Relevant bibliographies by topics / CNN / Journal articles

Journal articles on the topic 'CNN'

To see the other types of publications on this topic, follow the link: 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:

Consult the top 50 journal articles for your research 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.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

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
11

Arena, P., S. Baglio, L. Fortuna, and G. Manganaro. "Chua's circuit can be generated by CNN cells." IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications 42, no. 2 (1995): 123–25. http://dx.doi.org/10.1109/81.372854.

Full text
APA, Harvard, Vancouver, ISO, and other styles
12

Maulenov, K. S., and S. A. Kudubaeva. "COMPARATIVEANALYSISOFFACEDETECTORSHAAR, HOG, CNN." SERIES PHYSICO-MATHEMATICAL 5, no. 339 (October 15, 2021): 74–82. http://dx.doi.org/10.32014/2021.2518-1726.87.

Full text
APA, Harvard, Vancouver, ISO, and other styles
13

Wang, Peng-Shuai, Chun-Yu Sun, Yang Liu, and Xin Tong. "Adaptive O-CNN." ACM Transactions on Graphics 37, no. 6 (January 10, 2019): 1–11. http://dx.doi.org/10.1145/3272127.3275050.

Full text
APA, Harvard, Vancouver, ISO, and other styles
14

Lule, Jack. "CNN at 25." Critical Studies in Media Communication 22, no. 4 (October 2005): 339. http://dx.doi.org/10.1080/07393180500288469.

Full text
APA, Harvard, Vancouver, ISO, and other styles
15

He, Kaiming, Georgia Gkioxari, Piotr Dollar, and Ross Girshick. "Mask R-CNN." IEEE Transactions on Pattern Analysis and Machine Intelligence 42, no. 2 (February 1, 2020): 386–97. http://dx.doi.org/10.1109/tpami.2018.2844175.

Full text
APA, Harvard, Vancouver, ISO, and other styles
16

Chua, L. O., and T. Roska. "The CNN paradigm." IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications 40, no. 3 (March 1993): 147–56. http://dx.doi.org/10.1109/81.222795.

Full text
APA, Harvard, Vancouver, ISO, and other styles
17

ITOH, MAKOTO, and LEON O. CHUA. "DESIGNING CNN GENES." International Journal of Bifurcation and Chaos 13, no. 10 (October 2003): 2739–824. http://dx.doi.org/10.1142/s0218127403008375.

Full text
Abstract:
A systematic design methodology for finding CNN parameters with prescribed functions is proposed. A given function (task) is translated into several local operations, and they are realized as stable states of the CNN system. Many CNN parameters (CNN genes) with the same functions can be easily derived by using this design methodology. A genetic algorithm based CNN gene design methodology is also proposed. Two new genetic "activation and inactivation" operations are introduced to generate CNN genes effectively. Many useful CNN genes can be obtained systematically from known genes by using these genetic operations. Furthermore, the signal propagation property for activated and inactivated CNN genes is studied.
APA, Harvard, Vancouver, ISO, and other styles
18

ITOH, MAKOTO, and LEON O. CHUA. "MULTIPURPOSE HYSTERESIS CNN." International Journal of Bifurcation and Chaos 14, no. 12 (December 2004): 4035–73. http://dx.doi.org/10.1142/s021812740401179x.

Full text
Abstract:
In this paper, we propose a multipurpose hysteresis CNN (cellular neural network) made of first-order cells with hysteresis switches. The hysteresis CNN has applications not only in image processing, but also in pattern formation, nonlinear wave propagation and associative and dynamic memories, because each hysteresis CNN cell has two operating modes, namely, a bistable multivibrator mode and a relaxation oscillator mode.
APA, Harvard, Vancouver, ISO, and other styles
19

Moyo, Last. "The CNN defect." Journal of International Communication 17, no. 2 (August 2011): 121–38. http://dx.doi.org/10.1080/13216597.2011.589365.

Full text
APA, Harvard, Vancouver, ISO, and other styles
20

DOGARU, RADU, and LEON O. CHUA. "UNIVERSAL CNN CELLS." International Journal of Bifurcation and Chaos 09, no. 01 (January 1999): 1–48. http://dx.doi.org/10.1142/s021812749900002x.

Full text
Abstract:
A cellular neural/nonlinear network (CNN) [Chua, 1998] is a biologically inspired system where computation emerges from a collection of simple nonlinear locally coupled cells. This paper reviews our recent research results beginning from the standard uncoupled CNN cell which can realize only linearly separable local Boolean functions, to a generalized universal CNN cell capable of realizing arbitrary Boolean functions. The key element in this evolutionary process is the replacement of the linear discriminant (offset) function w(σ)=σ in the "standard" CNN cell in [Chua, 1998] by a piecewise-linear function defined in terms of only absolute value functions. As in the case of the standard CNN cells, the excitation σ evaluates the correlation between a given input vector u formed by the outputs of the neighboring cells, and a template vector b, which is interpreted in this paper as an orientation vector. Using the theory of canonical piecewise-linear functions [Chua & Kang, 1977], the discriminant function [Formula: see text] is found to guarantee universality and its parameters can be easily determined. In this case, the number of additional parameters and absolute value functions m is bounded by m<2n-1, where n is the number of all inputs (n=9 for a 3×3 template). An even more compact representation where m<n-1 is also presented which is based on a special form of a piecewise-linear function; namely, a multi-nested discriminant: w (σ) =s (zm +| zm -1 +⋯ | z1 +| z0 +σ |||). Using this formula, the "benchmark" Parity function with an arbitrary number of inputs n is found to have an analytical solution with a complexity of only m =O ( log 2 (n)).
APA, Harvard, Vancouver, ISO, and other styles
21

Shree G, Gana, Afreen Khanam, Bhavana N.P, Divyashree K.M, Akshay K.S, and Shruthi U. "Traffic_Sign_Classification Using CNN." International Journal of Research Publication and Reviews 03, no. 12 (2022): 1981–86. http://dx.doi.org/10.55248/gengpi.2022.31262.

Full text
Abstract:
Autonomous driving cars are booming these days and the demand for a robust traffic sign recognition system that assures safety by recognizing traffic signs accurately and fast is increasing. We all must have heard about self-driving cars in which the passenger can fully depend on the car for traveling. But to achieve level 5 autonomy, it is necessary for all the vehicles to understand and follow the traffic rules. In the global world of Artificial Intelligence (AI) and advancement in technologies, many researchers and big companies like Tesla, Uber, Google, Mercedes-Benz, Toyota, Ford, Audi, etc are working on autonomous vehicles and self-driving cars Here in this paper we planned to use CNN (convolution_neural_network) algorithm is a part of a deep learning model to classify the images present in the dataset into different categories. It can classify 43 different signs of traffic from the German Traffic Sign Recognition benchmark dataset.
APA, Harvard, Vancouver, ISO, and other styles
22

Shujaat, Muhammad, Abdul Wahab, Hilal Tayara, and Kil To Chong. "pcPromoter-CNN: A CNN-Based Prediction and Classification of Promoters." Genes 11, no. 12 (December 21, 2020): 1529. http://dx.doi.org/10.3390/genes11121529.

Full text
Abstract:
A promoter is a small region within the DNA structure that has an important role in initiating transcription of a specific gene in the genome. Different types of promoters are recognized by their different functions. Due to the importance of promoter functions, computational tools for the prediction and classification of a promoter are highly desired. Promoters resemble each other; therefore, their precise classification is an important challenge. In this study, we propose a convolutional neural network (CNN)-based tool, the pcPromoter-CNN, for application in the prediction of promotors and their classification into subclasses σ70, σ54, σ38, σ32, σ28 and σ24. This CNN-based tool uses a one-hot encoding scheme for promoter classification. The tools architecture was trained and tested on a benchmark dataset. To evaluate its classification performance, we used four evaluation metrics. The model exhibited notable improvement over that of existing state-of-the-art tools.
APA, Harvard, Vancouver, ISO, and other styles
23

Lee, Hyungtae, Sungmin Eum, and Heesung Kwon. "ME R-CNN: Multi-Expert R-CNN for Object Detection." IEEE Transactions on Image Processing 29 (2020): 1030–44. http://dx.doi.org/10.1109/tip.2019.2938879.

Full text
APA, Harvard, Vancouver, ISO, and other styles
24

Groshek, Jacob. "Homogenous Agendas, Disparate Frames: CNN and CNN International Coverage Online." Journal of Broadcasting & Electronic Media 52, no. 1 (February 26, 2008): 52–68. http://dx.doi.org/10.1080/08838150701820809.

Full text
APA, Harvard, Vancouver, ISO, and other styles
25

Shao, Tianjia, Yin Yang, Yanlin Weng, Qiming Hou, and Kun Zhou. "H-CNN: Spatial Hashing Based CNN for 3D Shape Analysis." IEEE Transactions on Visualization and Computer Graphics 26, no. 7 (July 1, 2020): 2403–16. http://dx.doi.org/10.1109/tvcg.2018.2887262.

Full text
APA, Harvard, Vancouver, ISO, and other styles
26

Shustanov, A. V., and P. Y. Yakimov. "Modification of single-purpose CNN for creating multi-purpose CNN." Journal of Physics: Conference Series 1368 (November 2019): 052036. http://dx.doi.org/10.1088/1742-6596/1368/5/052036.

Full text
APA, Harvard, Vancouver, ISO, and other styles
27

Kumar, Sumit, and Satish Kumar Singh. "Occluded Thermal Face Recognition Using Bag of CNN ($Bo$CNN)." IEEE Signal Processing Letters 27 (2020): 975–79. http://dx.doi.org/10.1109/lsp.2020.2996429.

Full text
APA, Harvard, Vancouver, ISO, and other styles
28

Anwar, Saeed, Nick Barnes, and Lars Petersson. "A Systematic Evaluation: Fine-Grained CNN vs. Traditional CNN Classifiers." Electronics 12, no. 23 (December 4, 2023): 4877. http://dx.doi.org/10.3390/electronics12234877.

Full text
Abstract:
Fine-grained classifiers collect information about inter-class variations to best use the underlying minute and subtle differences. The task is challenging due to the minor differences between the colors, viewpoints, and structure in the same class entities. The classification becomes difficult and challenging due to the similarities between the differences in viewpoint with other classes and its own. This work investigates the performance of landmark traditional CNN classifiers, presenting top-notch results on large-scale classification datasets and comparing them against state-of-the-art fine-grained classifiers. This paper poses three specific questions. (i) Do the traditional CNN classifiers achieve comparable results to fine-grained classifiers? (ii) Do traditional CNN classifiers require any specific information to improve fine-grained ones? (iii) Do current traditional state-of-the-art CNN classifiers improve the fine-grained classification while utilized as a backbone? Therefore, we train the general CNN classifiers throughout this work without introducing any aspect specific to fine-grained datasets. We show an extensive evaluation on six datasets to determine whether the fine-grained classifier can elevate the baseline in their experiments. We provide ablation studies regarding efficiency, number of parameters, flops, and performance.
APA, Harvard, Vancouver, ISO, and other styles
29

Ding, Yi-hong, Jin-long Liu, Xu-ri Huang, Ze-sheng Li, and Chia-chung Sun. "C4N: The first CnN radical with stable cyclic isomers." Journal of Chemical Physics 114, no. 12 (March 22, 2001): 5170–79. http://dx.doi.org/10.1063/1.1351884.

Full text
APA, Harvard, Vancouver, ISO, and other styles
30

Sassi, Ameni, Wael Ouarda, Chokri Ben Amar, and Serge Miguet. "Sky-CNN: A CNN-based Learning Approach for Skyline Scene Understanding." International Journal of Intelligent Systems and Applications 11, no. 4 (April 8, 2019): 14–25. http://dx.doi.org/10.5815/ijisa.2019.04.02.

Full text
APA, Harvard, Vancouver, ISO, and other styles
31

Tripathy, Santosh Kumar, and Rajeev Srivastava. "AMS-CNN: Attentive multi-stream CNN for video-based crowd counting." International Journal of Multimedia Information Retrieval 10, no. 4 (October 31, 2021): 239–54. http://dx.doi.org/10.1007/s13735-021-00220-7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
32

Tajalsir, Mohammed, Susana Mu˜noz Hern´andez, and Fatima Abdalbagi Mohammed. "ASERS-CNN: Arabic Speech Emotion Recognition System based on CNN Model." Signal & Image Processing : An International Journal 13, no. 1 (February 28, 2022): 45–53. http://dx.doi.org/10.5121/sipij.2022.13104.

Full text
Abstract:
When two people are on the phone, although they cannot observe the other person's facial expression and physiological state, it is possible to estimate the speaker's emotional state by voice roughly. In medical care, if the emotional state of a patient, especially a patient with an expression disorder, can be known, different care measures can be made according to the patient's mood to increase the amount of care. The system that capable for recognize the emotional states of human being from his speech is known as Speech emotion recognition system (SER). Deep learning is one of most technique that has been widely used in emotion recognition studies, in this paper we implement CNN model for Arabic speech emotion recognition. We propose ASERS-CNN model for Arabic Speech Emotion Recognition based on CNN model. We evaluated our model using Arabic speech dataset named Basic Arabic Expressive Speech corpus (BAES-DB). In addition of that we compare the accuracy between our previous ASERS-LSTM and new ASERS-CNN model proposed in this paper and we comes out that our new proposed mode is outperformed ASERS-LSTM model where it get 98.18% accuracy.
APA, Harvard, Vancouver, ISO, and other styles
33

Gao, Fei, Teresa Wu, Jing Li, Bin Zheng, Lingxiang Ruan, Desheng Shang, and Bhavika Patel. "SD-CNN: A shallow-deep CNN for improved breast cancer diagnosis." Computerized Medical Imaging and Graphics 70 (December 2018): 53–62. http://dx.doi.org/10.1016/j.compmedimag.2018.09.004.

Full text
APA, Harvard, Vancouver, ISO, and other styles
34

Zavala-Mondragon, Luis A., Bishal Lamichhane, Lu Zhang, and Gerard de Haan. "CNN-SkelPose: a CNN-based skeleton estimation algorithm for clinical applications." Journal of Ambient Intelligence and Humanized Computing 11, no. 6 (February 28, 2019): 2369–80. http://dx.doi.org/10.1007/s12652-019-01259-5.

Full text
APA, Harvard, Vancouver, ISO, and other styles
35

加藤, 茂. "ガスタングステンアーク溶接とCNN（Gas Tungsten Arc Welding and CNN）." Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 34, no. 3 (August 15, 2022): 110. http://dx.doi.org/10.3156/jsoft.34.3_110_2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
36

Wan, Yi, Xianzhong Xie, Junfan Chen, Kunpeng Xie, Dezhi Yi, Ye Lu, and Keke Gai. "ADS-CNN: Adaptive Dataflow Scheduling for lightweight CNN accelerator on FPGAs." Future Generation Computer Systems 158 (September 2024): 138–49. http://dx.doi.org/10.1016/j.future.2024.04.038.

Full text
APA, Harvard, Vancouver, ISO, and other styles
37

MA, Tatyana Yu, SERGEY V. BOBROV, and NATALYA M. ZALESOVA. "BIBLICAL PHRASEOLOGY IN CNN PUBLICATIONS." Theoretical and Applied Linguistics, no. 4 (2020): 94–103. http://dx.doi.org/10.22250/2410-7190_2020_6_4_94_103.

Full text
Abstract:
This paper presents the results of the study of biblical phraseological units (BPUs) found in CNN publications during the period of 2015-2019 (the total of 1643 articles). At the first stage of the experiment, the analysis of 156 BPUs used in the articles demonstrated different distribution of the tokens in CNN rubrics. It was discovered that BPUs in the rubrics “Politics” and “Entertainment” were characterized by considerably higher frequency of occurrence than those in “Style” and “Sports”. At the second stage, specifically designed questionnaire was given to 30 American native speakers to determine the perceptual boundaries of the Bible words. The obtained data revealed indirect correlation between phraseological units frequency of occurrence and the American speakers’ awareness degree of their associative connection with the original source - the Bible: the higher the awareness, the lower the frequency of occurrence. The obtained results enable to assume that the readers do not always identify these units as part of the Holy Scripture, because some BPUs lose their sacred connotations over time. However, journalists often use such units as stylistic means due to their imaginative stylistic and evaluation potential.
APA, Harvard, Vancouver, ISO, and other styles
38

KILIÇ, RECAI. "CHAOS SYNCHRONIZATION IN SC-CNN-BASED CIRCUIT AND AN INTERESTING INVESTIGATION: CAN A SC-CNN-BASED CIRCUIT BEHAVE SYNCHRONOUSLY WITH THE ORIGINAL CHUA'S CIRCUIT?" International Journal of Bifurcation and Chaos 14, no. 03 (March 2004): 1071–83. http://dx.doi.org/10.1142/s0218127404009600.

Full text
Abstract:
In this work, after giving a complete verification of the continuous synchronization between two identical SC-CNN-based circuits depending on the driving variable, we have investigated the continuous synchronization phenomenon between SC-CNN-based circuit and Chua's circuit. PSpice simulation results confirm that SC-CNN-based circuit can behave synchronously with Chua's circuit in the case when very accurate parameter equalities are provided.
APA, Harvard, Vancouver, ISO, and other styles
39

Jamil, Nursuriati, Ali Abd Almisreb, Syed Mohd Zahid Syed Zainal Ariffin, N. Md Din, and Raseeda Hamzah. "Can Convolution Neural Network (CNN) Triumph in Ear Recognition of Uniform Illumination Invariant?" Indonesian Journal of Electrical Engineering and Computer Science 11, no. 2 (August 1, 2018): 558. http://dx.doi.org/10.11591/ijeecs.v11.i2.pp558-566.

Full text
Abstract:
Current deep convolution neural network (CNN) has shown to achieve superior performance on a number of computer vision tasks such as image recognition, classification and object detection. The deep network was also tested for view-invariance, robustness and illumination invariance. However, the CNN architecture has thus far only been tested on non-uniform illumination invariant. Can CNN perform equally well for very underexposed or overexposed images or known as uniform illumination invariant? This is the gap that we are addressing in this paper. In our work, we collected ear images under different uniform illumination conditions with lumens or lux values ranging from 2 lux to 10,700 lux. A total of 1,100 left and right ear images from 55 subjects are captured under natural illumination conditions. As CNN requires considerably large amount of data, the ear images are further rotated at every 5o angles to generate 25,300 images. For each subject, 50 images are used as validation/testing dataset, while the remaining images are used as training datasets. Our proposed CNN model is then trained from scratch and validation and testing results showed recognition accuracy of 97%. The results showed that 100% accuracy is achieved for images with lumens ranging above 30 but having problem with lumens less than 10 lux
APA, Harvard, Vancouver, ISO, and other styles
40

Choi, Jiwoo, Sangil Choi, and Taewon Kang. "Personal Identification CNN Model using Gait Cycle." Journal of Korean Institute of Information Technology 20, no. 11 (November 30, 2022): 127–36. http://dx.doi.org/10.14801/jkiit.2022.20.11.127.

Full text
APA, Harvard, Vancouver, ISO, and other styles
41

Sheikh, Sohail. "Face Recognition Using Cnn." International Journal for Research in Applied Science and Engineering Technology 6, no. 3 (March 31, 2018): 1411–14. http://dx.doi.org/10.22214/ijraset.2018.3218.

Full text
APA, Harvard, Vancouver, ISO, and other styles
42

Wathan, M. Hizbul. "Shallots Classification using CNN." International Journal of Informatics and Computation 3, no. 2 (May 25, 2022): 50. http://dx.doi.org/10.35842/ijicom.v3i2.41.

Full text
Abstract:
Shallots are an essential plant for the commercial and home industries included in the Allium genus. Choosing the type of onion based on the characteristics is very easy for humans to do but not easy for humans to do in the spice industry; therefore, machines will replace human limitations in recognizing the type of shallots in the spice industry. Inspired by the success of research on the classification of shallots using SVM, we propose CNN to tackle the problem of classifying types of shallots based on shape and texture features. This study uses the CNN method's performance to categorize different varieties of shallots based on their shape and texture features. In a shallot classification test, our approach promises higher accuracy and lower loss than standard machine techniques.
APA, Harvard, Vancouver, ISO, and other styles
43

V S, Amar. "Autonomous Driving using CNN." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 30, 2021): 3633–36. http://dx.doi.org/10.22214/ijraset.2021.35771.

Full text
Abstract:
Human beings are currently addicted to automation and robotics technologies. The state-of-the-art in deep learning technologies and AI is the subject of this autonomous driving. Driving with automated driving systems promises to be safe, enjoyable, and efficient.. It is preferable to train in a virtual environment first and then move to a real-world one. Its goal is to enable a vehicle to recognise its surroundings and navigate without the need for human intervention. The raw pixels from a single front-facing camera were directly transferred to driving commands using a convolution neural network (CNN). This end-to-end strategy proved to be remarkably effective, The system automatically learns internal representations of the essential processing stages such as detecting useful road components using only the human steering angle as the training signal. We never expressly taught it to recognise the contour of roadways, for example. In comparison to explicit issue decomposition, such as lane marking detection, Our end-to-end solution optimises all processing processes at the same time, including path planning and control. We believe that this will lead to improved performance and smaller systems in the long run. Internal components will self-optimize to maximise overall system performance, resulting in improved performance.
APA, Harvard, Vancouver, ISO, and other styles
44

Robinson, Piers. "The CNN Effect Revisited." Critical Studies in Media Communication 22, no. 4 (October 2005): 344–49. http://dx.doi.org/10.1080/07393180500288519.

Full text
APA, Harvard, Vancouver, ISO, and other styles
45

Jones, Alex. "CNN and September 11th." Harvard International Journal of Press/Politics 7, no. 2 (April 2002): 6–16. http://dx.doi.org/10.1177/1081180x0200700202.

Full text
APA, Harvard, Vancouver, ISO, and other styles
46

Meesters, Ybe, Danielle Starreveld, Esmée Verwijk, Harm-Pieter Spaans, and Marijke C. M. Gordijn. "Chronotherapy Network Netherlands (CNN)." Journal of Biological Rhythms 35, no. 3 (December 30, 2019): 317–19. http://dx.doi.org/10.1177/0748730419896503.

Full text
APA, Harvard, Vancouver, ISO, and other styles
47

Berkowitz, Dan, and David Asa Schwartz. "Miley, CNN andThe Onion." Journalism Practice 10, no. 1 (February 16, 2015): 1–17. http://dx.doi.org/10.1080/17512786.2015.1006933.

Full text
APA, Harvard, Vancouver, ISO, and other styles
48

Williams, J. "Avoiding the CNN moment." IT Professional 3, no. 2 (2001): 72, 68–70. http://dx.doi.org/10.1109/6294.918228.

Full text
APA, Harvard, Vancouver, ISO, and other styles
49

Steffens, Cristiano R., Lucas R. V. Messias, Paulo J. L. Drews-Jr, and Silvia S. d. C. Botelho. "CNN Based Image Restoration." Journal of Intelligent & Robotic Systems 99, no. 3-4 (January 11, 2020): 609–27. http://dx.doi.org/10.1007/s10846-019-01124-9.

Full text
APA, Harvard, Vancouver, ISO, and other styles
50

Hänggi, M., and G. S. Moschytz. "Visualisation of CNN dynamics." Electronics Letters 33, no. 20 (1997): 1714. http://dx.doi.org/10.1049/el:19971125.

Full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the bibliographies on the topic 'CNN' for other source types:
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