Relevant bibliographies by topics / CNN

Academic literature on the topic 'CNN'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 May 2024

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Contents

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'CNN.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "CNN"

1

Sylvester, Judith, and Suzanne Huffman. "CNN." Newspaper Research Journal 24, no. 1 (January 2003): 22–30. http://dx.doi.org/10.1177/073953290302400102.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Bertoni, Federico, Giovanna Citti, and Alessandro Sarti. "LGN-CNN: A biologically inspired CNN architecture." Neural Networks 145 (January 2022): 42–55. http://dx.doi.org/10.1016/j.neunet.2021.09.024.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Bertoni, Federico, Giovanna Citti, and Alessandro Sarti. "LGN-CNN: A biologically inspired CNN architecture." Neural Networks 145 (January 2022): 42–55. http://dx.doi.org/10.1016/j.neunet.2021.09.024.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Zimmermann, Patricia R. "Beyond CNN." Afterimage 33, no. 2 (September 2005): 15–16. http://dx.doi.org/10.1525/aft.2005.33.2.15.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Zhan, Zhiwei, Guoliang Liao, Xiang Ren, Guangsi Xiong, Weilin Zhou, Wenchao Jiang, and Hong Xiao. "RA-CNN." International Journal of Software Science and Computational Intelligence 14, no. 1 (January 1, 2022): 1–14. http://dx.doi.org/10.4018/ijssci.311446.

Full text
Abstract:
Emotion is a feeling that can be expressed by different mediums. Emotion analysis is a key task in NLP which is responsible for judging the emotional tendency of texts. Currently, in a complex multi-semantic environment, it still suffers from poor performance. Traditional methods usually require human intervention, while deep learning always has a trade-off between local and global features. To solve the problem that deep learning models generalize poorly for emotion analysis, this article proposed a semantic-enhanced method called RA-CNN, a classification model under a multi-semantic environment. It integrates CNN for local feature extraction, RNN for global feature extraction, and attention mechanism for feature scaling. As a result, it can acquire the correct meaning of sentences. After experimenting with the hotel review dataset, it has an improvement in positive feeling classification compared with the baseline model (3%~13%), and it showed a competitive performance compared with ordinary deep learning models (~1%). On negative feeling classification, it also performed well close to other models.
APA, Harvard, Vancouver, ISO, and other styles
6

Khaydarova, Rezeda, Dmitriy Mouromtsev, Vladislav Fishchenko, Vladislav Shmatkov, Maxim Lapaev, and Ivan Shilin. "ROCK-CNN." International Journal of Embedded and Real-Time Communication Systems 12, no. 3 (July 2021): 14–31. http://dx.doi.org/10.4018/ijertcs.2021070102.

Full text
Abstract:
The paper is dedicated to distributed convolutional neural networks on a resource constrained devices cluster. The authors focus on requirements that meet the users' needs. Based on this, architecture of the system is proposed. Two use cases of CNN computations on a ROCK-CNN cluster are mentioned, and algorithms for organizing distributed convolutional neural networks are described. Experiments to validate proposed architecture and algorithms for distributed deep learning computations are conducted as well.
APA, Harvard, Vancouver, ISO, and other styles
7

Wang, Peng-Shuai, Yang Liu, Yu-Xiao Guo, Chun-Yu Sun, and Xin Tong. "O-CNN." ACM Transactions on Graphics 36, no. 4 (July 20, 2017): 1–11. http://dx.doi.org/10.1145/3072959.3073608.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Hayworth, Gene. "CNN/Money." Journal of Business & Finance Librarianship 10, no. 3 (July 7, 2005): 53–60. http://dx.doi.org/10.1300/j109v10n03_06.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Manatunga, Dilan, Hyesoon Kim, and Saibal Mukhopadhyay. "SP-CNN: A Scalable and Programmable CNN-Based Accelerator." IEEE Micro 35, no. 5 (September 2015): 42–50. http://dx.doi.org/10.1109/mm.2015.121.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Kaur, Kamaljit, and Parminder Kaur. "BERT-CNN: Improving BERT for Requirements Classification using CNN." Procedia Computer Science 218 (2023): 2604–11. http://dx.doi.org/10.1016/j.procs.2023.01.234.

Full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "CNN"

1

Garbay, Thomas. "Zip-CNN." Electronic Thesis or Diss., Sorbonne université, 2023. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2023SORUS210.pdf.

Full text
Abstract:
Les systèmes numériques utilisés pour l'Internet des Objets (IoT) et les Systèmes Embarqués ont connu une utilisation croissante ces dernières décennies. Les systèmes embarqués basés sur des microcontrôleurs (MCU) permettent de résoudre des problématiques variées, en récoltant de nombreuses données. Aujourd'hui, environ 250 milliards de MCU sont utilisés. Les projections d'utilisation de ces systèmes pour les années à venir annoncent une croissance très forte. L'intelligence artificielle a connu un regain d'intérêt dans les années 2012. L'utilisation de réseaux de neurones convolutifs (CNN) a permis de résoudre de nombreuses problématiques de vision par ordinateur ou de traitement du langage naturel. L'utilisation de ces algorithmes d'intelligence artificielle au sein de systèmes embarqués permettrait d'améliorer grandement l'exploitation des données récoltées. Cependant le coût d'exécution des CNN rend leur implémentation complexe au sein de systèmes embarqués. Ces travaux de thèse se concentrent sur l'exploration de l'espace des solutions pour guider l'intégration des CNN au sein de systèmes embarqués basés sur des microcontrôleurs. Pour cela, la méthodologie ZIP-CNN est définie. Elle tient compte du système embarqué et du CNN à implémenter. Elle fournit à un concepteur des informations sur l'impact de l'exécution du CNN sur le système. Un modèle fourni quantitativement une estimation de la latence, de la consommation énergétique et de l'espace mémoire nécessaire à une inférence d'un CNN au sein d'une cible embarquée, quelle que soit la topologie du CNN. Ce modèle tient compte des éventuelles réductions algorithmiques telles que la distillation de connaissances, l'élagage ou la quantification. L'implémentation de CNN de l'état de l'art au sein de MCU a permis la validation expérimentale de la justesse de l'approche. L'utilisation des modèles développés durant ces travaux de thèse démocratise l'implémentation de CNN au sein de MCU, en guidant les concepteurs de systèmes embarqués. De plus, les résultats obtenus ouvrent une voie d'exploration pour appliquer les modèles développés à d'autres matériels cibles, comme les architectures multi-cœur ou les FPGA. Les résultats d'estimations sont également exploitables dans l'utilisation d'algorithmes de recherche de réseaux de neurones (NAS)
Digital systems used for the Internet of Things (IoT) and Embedded Systems have seen an increasing use in recent decades. Embedded systems based on Microcontroller Unit (MCU) solve various problems by collecting a lot of data. Today, about 250 billion MCU are in use. Projections in the coming years point to very strong growth. Artificial intelligence has seen a resurgence of interest in 2012. The use of Convolutional Neural Networks (CNN) has helped to solve many problems in computer vision or natural language processing. The implementation of CNN within embedded systems would greatly improve the exploitation of the collected data. However, the inference cost of a CNN makes their implementation within embedded systems challenging. This thesis focuses on exploring the solution space, in order to assist the implementation of CNN within embedded systems based on microcontrollers. For this purpose, the ZIP-CNN methodology is defined. It takes into account the embedded system and the CNN to be implemented. It provides an embedded designer with information regarding the impact of the CNN inference on the system. A designer can explore the impact of design choices, with the objective of respecting the constraints of the targeted application. A model is defined to quantitatively provide an estimation of the latency, the energy consumption and the memory space required to infer a CNN within an embedded target, whatever the topology of the CNN is. This model takes into account algorithmic reductions such as knowledge distillation, pruning or quantization. The implementation of state-of-the-art CNN within MCU verified the accuracy of the different estimations through an experimental process. This thesis democratize the implementation of CNN within MCU, assisting the designers of embedded systems. Moreover, the results open a way of exploration to apply the developed models to other target hardware, such as multi-core architectures or FPGA. The estimation results are also exploitable in the Neural Architecture Search (NAS)
APA, Harvard, Vancouver, ISO, and other styles
2

Carpani, Valerio. "CNN-based video analytics." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018.

Find full text
Abstract:
The content of this thesis illustrates the six months work done during my internship at TKH Security Solutions - Siqura B.V. in Gouda, Netherlands. The aim of this thesis is to investigate on convolutional neural networks possible usage, from two different point of view: first we propose a novel algorithm for person re-identification, second we propose a deployment chain, for bringing research concepts to product ready solutions. In existing works, the person re-identification task is assumed to be independent of the person detection task. In this thesis instead, we consider the two tasks as linked. In fact, features produced by an object detection convolutional neural network (CNN) contain useful information, which is not being used by current re-identification methods. We propose several solutions for learning a metric on CNN features to distinguish between different identities. Then the best of these solutions is compared with state of the art alternatives on the popular Market-1501 dataset. Results show that our method outperforms them in computational efficiency, with only a reasonable loss in accuracy. For this reason, we believe that the proposed method can be more appropriate than current state of the art methods in situations where the computational efficiency is critical, such as embedded applications. The deployment chain we propose in this thesis has two main goals: it must be flexible for introducing new advancement in networks architecture, and it must be able to deploy neural networks both on server and embedded platforms. We tested several frameworks on several platforms and we ended up with a deployment chain that relies on the open source format ONNX.
APA, Harvard, Vancouver, ISO, and other styles
3

Lara, Teodoro. "Controllability and applications of CNN." Diss., Georgia Institute of Technology, 1997. http://hdl.handle.net/1853/28921.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Samal, Kruttidipta. "FPGA acceleration of CNN training." Thesis, Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/54467.

Full text
Abstract:
This thesis presents the results of an architectural study on the design of FPGA- based architectures for convolutional neural networks (CNNs). We have analyzed the memory access patterns of a Convolutional Neural Network (one of the biggest networks in the family of deep learning algorithms) by creating a trace of a well-known CNN architecture and by developing a trace-driven DRAM simulator. The simulator uses the traces to analyze the effect that different storage patterns and dissonance in speed between memory and processing element, can have on the CNN system. This insight is then used create an initial design for a layer architecture for the CNN using an FPGA platform. The FPGA is designed to have multiple parallel-executing units. We design a data layout for the on-chip memory of an FPGA such that we can increase parallelism in the design. As the number of these parallel units (and hence parallelism) depends on the memory layout of input and output, particularly if parallel read and write accesses can be scheduled or not. The on-chip memory layout minimizes access contention during the operation of parallel units. The result is an SoC (System on Chip) that acts as an accelerator and can have more number of parallel units than previous work. The improvement in design was also observed by comparing post synthesis loop latency tables between our design and one with a single unit design. This initial design can help in designing FPGAs targeted for deep learning algorithms that can compete with GPUs in terms of performance.
APA, Harvard, Vancouver, ISO, and other styles
5

Mohamed, Moussa Elmokhtar. "Conversion d’écriture hors-ligne en écriture en-ligne et réseaux de neurones profonds." Electronic Thesis or Diss., Nantes Université, 2024. http://www.theses.fr/2024NANU4001.

Full text
Abstract:
Cette thèse se focalise sur la conversion d’images statiques d’écriture hors- ligne en signaux temporels d’écriture en-ligne. L’objectif est d’étendre l’approche à réseau de neurone au-delà des images de lettres isolées ainsi que de les généraliser à d’autres types de contenus plus complexes. La thèse explore deux approches neuronales distinctes, la première approche est un réseau de neurones convolutif entièrement convolutif multitâche UNet basé sur la méthode de [ZYT18]. Cette approche a démontré des bons résultats de squelettisation mais en revanche une extraction de trait problé- matique. En raison des limitations de modélisation temporelle intrinsèque à l’architecture CNN. La deuxième approche s’appuie sur le modèle de squelettisation précédent pour ex- traire les sous-traits et propose une modélisation au niveau sous-traits avec deux Tranformers : un encodeur de sous-trait (SET) et un décodeur pour ordonner les sous-traits (SORT) à l’aide de leur vecteur descripteur ainsi que la prédiction de lever de stylo. Cette approche surpasse l’état de l’art sur les bases de données de mots, phrases et d’équations mathématiques et a permis de surmonter plusieurs limitations relevées dans la littérature. Ces avancées ont permis d’étendre la portée de la conversion d’image d’écriture hors- ligne vers l’écriture en-ligne pour inclure des phrases entières de texte et d’aborder un type de contenu complexe tel que les équations mathématiques
This thesis focuses on the conversion of static images of offline handwriting into temporal signals of online handwriting. Our goal is to extend neural networks beyond the scale of images of isolated letters and as well to generalize to other complex types of content. The thesis explores two distinct neural network-based approaches, the first approach is a fully convolutional multitask UNet-based network, inspired by the method of [ZYT18]. This approach demonstrated good results for skeletonization but suboptimal stroke extrac- tion. Partly due to the inherent temporal mod- eling limitations of CNN architecture. The second approach builds on the pre- vious skeletonization model to extract sub- strokes and proposes a sub-stroke level modeling with Transformers, consisting of a sub- stroke embedding transformer (SET) and a sub-stroke ordering transformer (SORT) to or- der the different sub-strokes as well as pen up predictions. This approach outperformed the state of the art on text lines and mathematical equations databases and addressed several limitations identified in the literature. These advancements have expanded the scope of offline-to-online conversion to include entire text lines and generalize to bidimensional content, such as mathematical equations
APA, Harvard, Vancouver, ISO, and other styles
6

Rossetto, Andrea. "CNN per view synthesis da mappe depth." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/16570/.

Full text
Abstract:
Breve introduzione alle reti neurali e al deep learning con descrizione dei sistemi utilizzati per i modelli e i test effettuati. Spiegazione del funzionamento dei sistemi creati ed esposizione dei risultati ottenuti.
APA, Harvard, Vancouver, ISO, and other styles
7

Castelli, Filippo Maria. "3D CNN methods in biomedical image segmentation." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/18796/.

Full text
Abstract:
A definite trend in Biomedical Imaging is the one towards the integration of increasingly complex interpretative layers to the pure data acquisition process. One of the most interesting and looked-forward goals in the field is the automatic segmentation of objects of interest in extensive acquisition data, target that would allow Biomedical Imaging to look beyond its use as a purely assistive tool to become a cornerstone in ambitious large-scale challenges like the extensive quantitative study of the Human Brain. In 2019 Convolutional Neural Networks represent the state of the art in Biomedical Image segmentation and scientific interests from a variety of fields, spacing from automotive to natural resource exploration, converge to their development. While most of the applications of CNNs are focused on single-image segmentation, biomedical image data -being it MRI, CT-scans, Microscopy, etc- often benefits from three-dimensional volumetric expression. This work explores a reformulation of the CNN segmentation problem that is native to the 3D nature of the data, with particular interest to the applications to Fluorescence Microscopy volumetric data produced at the European Laboratories for Nonlinear Spectroscopy in the context of two different large international human brain study projects: the Human Brain Project and the White House BRAIN Initiative.
APA, Harvard, Vancouver, ISO, and other styles
8

Ringenson, Josefin. "Efficiency of CNN on Heterogeneous Processing Devices." Thesis, Linköpings universitet, Programvara och system, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-155034.

Full text
Abstract:
In the development of advanced driver assistance systems, computer vision problemsneed to be optimized to run efficiently on embedded platforms. Convolutional neural network(CNN) accelerators have proven to be very efficient for embedded camera platforms,such as the ones used for automotive vision systems. Therefore, the focus of this thesisis to evaluate the efficiency of a CNN on a future embedded heterogeneous processingdevice. The memory size in an embedded system is often very limited, and it is necessary todivide the input into multiple tiles. In addition, there are power and speed constraintsthat needs to be met to be able to use a computer vision system in a car. To increaseefficiency and optimize the memory usage, different methods for CNN layer fusion areproposed and evaluated for a variety of tile sizes. Several different layer fusion methods and input tile sizes are chosen as optimal solutions,depending on the depth of the layers in the CNN. The solutions investigated inthe thesis are most efficient for deep CNN layers, where the number of channels is high.
APA, Harvard, Vancouver, ISO, and other styles
9

Kristin, Hallberg. "Islam, BBC och CNN : Palestinska inbördeskriget 2006-2007." Thesis, Uppsala universitet, Teologiska institutionen, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-295888.

Full text
Abstract:
The topic of this paper is how CNN and BBC, two of the largest media companies in the world, presented Islam in the Palestinian civil war during the years 2006-2007. Articles that CNN and BBC published on the Palestinian civil war have been analyzed in order to answer this question. The purpose is to see if Islam is portrayed in an Islamophobic way by CNN and BBC and if it is possible to find discursive tracks from Clash of Civilizations-theory in the analyzed articles. The findings indicate that there are elements of Islamophobia and discursive tracks of Clash of Civilizations when it comes to presenting islam during the Palestinian civil war. Another conclusion is also that CNN and BBC presented islam in different ways during the civil war.
APA, Harvard, Vancouver, ISO, and other styles
10

Eklund, Anton. "Cascade Mask R-CNN and Keypoint Detection used in Floorplan Parsing." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-415371.

Full text
Abstract:
Parsing floorplans have been a problem in automatic document analysis for long and have up until recent years been approached with algorithmic methods. With the rise of convolutional neural networks (CNN), this problem too has seen an upswing in performance. In this thesis the task is to recover, as accurately as possible, spatial and geometric information from floorplans. This project builds around instance segmentation models like Cascade Mask R-CNN to extract the bulk of information from a floorplan image. To complement the segmentation, a new style of using keypoint-CNN is presented to find precise locations of corners. These are then combined in a post-processing step to give the resulting segmentation. The resulting segmentation scores exceed the current baseline of the CubiCasa5k floorplan dataset with a mean IoU of 72.7% compared to 57.5%. Further, the mean IoU for individual classes is also improved for almost every class. It is also shown that Cascade Mask R-CNN is better suited than Mask R-CNN for this task.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "CNN"

1

Step by step ting dong CNN: Master listening with CNN news. Taibei Shi: Xi bo lun gu fen you xian gong si, 2011.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
2

The story of CNN. Mankato, MN: Creative Education, 2012.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
3

Whittemore, Hank. CNN: The inside story. Boston: Little, Brown, 1990.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
4

Aḥmad, Ibrāhīm. Ṭifl al-CNN: [riwāyah]. al-Suwayd: Dār al-Manfá, 1996.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
5

Linzhao, Wang, ed. Qing song ting dong CNN ru men ban: CNN listening comprehension edition. Taibei Shi: Xi bo lun gu fen you xian gong si, 2004.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
6

Bahador, Babak. The CNN Effect in Action. New York: Palgrave Macmillan US, 2007. http://dx.doi.org/10.1057/9780230604223.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Losure, Bob. Five Seconds to Air: Broadcast Journalism Behind the Scenes. Franklin, Tennessee: Hillsboro Press, 1998.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
8

CNN et la mondialisation de l'imaginaire. Paris: CNRS éditions, 2000.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
9

Lemon, Don. Transparent: CNN anchor and special correspondent. Las Vegas: Farrah Gray Pub., 2011.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
10

CNN World Report: Ted Turner's international news coup. London: J. Libbey, 1992.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Book chapters on the topic "CNN"

1

Norris, Donald J. "CNN demonstrations." In Machine Learning with the Raspberry Pi, 335–85. Berkeley, CA: Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-5174-4_6.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Manganaro, Gabriele, Paolo Arena, and Luigi Fortuna. "CNN Basics." In Cellular Neural Networks, 3–23. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-60044-9_1.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Robinson, Piers. "CNN effect." In Visual Global Politics, 62–67. Abingdon, Oxon ; New York, NY : Routledge, 2018. | Series: Interventions: Routledge, 2018. http://dx.doi.org/10.4324/9781315856506-7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Bahador, Babak. "The CNN Effect." In The CNN Effect in Action, 3–19. New York: Palgrave Macmillan US, 2007. http://dx.doi.org/10.1057/9780230604223_1.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Hänggi, Martin, and George S. Moschytz. "CNN Settling Time." In Cellular Neural Networks, 47–81. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4757-3220-7_4.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Manaswi, Navin Kumar. "CNN in TensorFlow." In Deep Learning with Applications Using Python, 97–104. Berkeley, CA: Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-3516-4_7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Manaswi, Navin Kumar. "CNN in Keras." In Deep Learning with Applications Using Python, 105–14. Berkeley, CA: Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-3516-4_8.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Yan, Wei Qi. "CNN and RNN." In Texts in Computer Science, 39–63. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-61081-4_3.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Allen, Kevin Lee. "CNN New Day." In Vectorworks for Entertainment Design, 293. Second edition. | New York: Routledge, 2020.: Routledge, 2020. http://dx.doi.org/10.4324/9780429290671-35.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Muñoz-Martínez, Francisco, José L. Abellán, and Manuel E. Acacio. "CNN-SIM: A Detailed Arquitectural Simulator of CNN Accelerators." In Euro-Par 2019: Parallel Processing Workshops, 720–24. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-48340-1_56.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "CNN"

1

Herruzo, P., M. Bolaños, and P. Radeva. "Can a CNN recognize Catalan diet?" In APPLICATION OF MATHEMATICS IN TECHNICAL AND NATURAL SCIENCES: 8th International Conference for Promoting the Application of Mathematics in Technical and Natural Sciences - AMiTaNS’16. Author(s), 2016. http://dx.doi.org/10.1063/1.4964956.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Talukdar, Chayanika, and Shikhar Kumar Sarma. "Assamese document classification using CNN, multi-channel CNN and CNN-SVM." In INTELLIGENT BIOTECHNOLOGIES OF NATURAL AND SYNTHETIC BIOLOGICALLY ACTIVE SUBSTANCES: XIV Narochanskie Readings. AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0179324.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Vinay, A., Desanur Naveen Reddy, Abhishek C. Sharma, S. Daksha, N. S. Bhargav, M. K. Kiran, K. N. B. Murthy, and S. Natrajan. "G-CNN and F-CNN: Two CNN based architectures for face recognition." In 2017 International Conference on Big Data Analytics and Computational Intelligence (ICBDAC). IEEE, 2017. http://dx.doi.org/10.1109/icbdaci.2017.8070803.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Xie, Lingxi, and Alan Yuille. "Genetic CNN." In 2017 IEEE International Conference on Computer Vision (ICCV). IEEE, 2017. http://dx.doi.org/10.1109/iccv.2017.154.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

SaiRam, K., Jayanta Mukherjee, Amit Patra, and Partha Pratim Das. "HSD-CNN." In ICVGIP 2018: 11th Indian Conference on Computer Vision, Graphics and Image Processing. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3293353.3293383.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Jin, Tian, and Seokin Hong. "Split-CNN." In ASPLOS '19: Architectural Support for Programming Languages and Operating Systems. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3297858.3304038.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Koo, Jamyoung, Junghoon Seo, Seunghyun Jeon, Jeongyeol Choe, and Taegyun Jeon. "RBox-CNN." In SIGSPATIAL '18: 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3274895.3274915.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Wang, Zheng, Zhuo Wang, Jian Liao, Chao Chen, Yongkui Yang, Bo Dong, Weiguang Chen, et al. "CNN-DMA." In GLSVLSI '21: Great Lakes Symposium on VLSI 2021. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3453688.3461496.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Ma, Fuyan, Ziyu Ma, Bin Sun, and Shutao Li. "TA-CNN." In MM '22: The 30th ACM International Conference on Multimedia. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3503161.3551587.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Wang, Lei, Meixiao Shen, Qian Chang, Ce Shi, Yuheng Zhou, and Jiantao Pu. "BG-CNN." In ICBIP '20: 2020 5th International Conference on Biomedical Signal and Image Processing. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3417519.3417560.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "CNN"

1

Flemming, Jens. What did the CNN learn? Westsächsische Hochschule Zwickau, November 2021. http://dx.doi.org/10.25366/2021.94.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Al-Allaf, Mohammed. US Wars and the CNN Factor. Fort Belvoir, VA: Defense Technical Information Center, April 2001. http://dx.doi.org/10.21236/ada441518.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Belknap, Margaret H. The CNN Effect: Stretegic Enabler or Operational Risk? Fort Belvoir, VA: Defense Technical Information Center, March 2001. http://dx.doi.org/10.21236/ada394687.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Kayaoglu, Barin. Why Turkish media is upset with CNN, WaPo. Al-Monitor: The Pulse of the Middle East, February 2017. http://dx.doi.org/10.26598/auis_ug_is_2017_02_02.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Baker, Jeffrey L. Achieving Operational Deception in the Age of CNN. Fort Belvoir, VA: Defense Technical Information Center, May 2003. http://dx.doi.org/10.21236/ada425945.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Sticht, Chris. Power System Waveform Classification Using Time-Frequency and CNN. Office of Scientific and Technical Information (OSTI), January 2022. http://dx.doi.org/10.2172/1841478.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Slavova, Angela, and Nikolay Kyurkchiev. On CNN Model of Black–Scholes Equation with Leland Correction. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, January 2018. http://dx.doi.org/10.7546/crabs.2018.02.03.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Slavova, Angela, and Nikolay Kyurkchiev. On CNN Model of Black–Scholes Equation with Leland Correction. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, February 2018. http://dx.doi.org/10.7546/grabs2018.2.03.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Kasupski, Bernard W., and III. CNN Effect: A Direct Path to the American Center of Gravity. Fort Belvoir, VA: Defense Technical Information Center, February 2000. http://dx.doi.org/10.21236/ada378514.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Belknap, Leslie H. Military Operations in the CNN World: Using the Media as a Force Multiplier. Fort Belvoir, VA: Defense Technical Information Center, February 1996. http://dx.doi.org/10.21236/ada307447.

Full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'CNN' for particular source types:
Journal articles Dissertations / Theses Books
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography