Open Access
Issue |
E3S Web of Conf.
Volume 469, 2023
The International Conference on Energy and Green Computing (ICEGC’2023)
|
|
---|---|---|
Article Number | 00069 | |
Number of page(s) | 11 | |
DOI | https://doi.org/10.1051/e3sconf/202346900069 | |
Published online | 20 December 2023 |
- MEMON, Jamshed, SAMI, Maira, KHAN, Rizwan Ahmed, et al. Handwritten optical character recognition (OCR): A comprehensive systematic literature review (SLR). IEEE Access, 2020, vol. 8, p. 142642-142668. [CrossRef] [Google Scholar]
- BALDOMINOS, Alejandro, SAEZ, Yago, et ISASI, Pedro. A survey of handwritten character recognition with mnist and emnist. Applied Sciences, 2019, vol. 9, no 15, p. 3169. [CrossRef] [Google Scholar]
- CHANDRA, Sushant, SISODIA, Saurav, et GUPTA, Preeti. Optical character recognition-A review. International Research Journal of Engineering and Technology (IRJET), 2020, vol. 7, no 4, p. 3037-3041. [Google Scholar]
- NGUYEN, Thi Tuyet Hai, JATOWT, Adam, COUSTATY, Mickael, et al. Survey of post-OCR processing approaches. ACM Computing Surveys (CSUR), 2021, vol. 54, no 6, p. 1-37. [CrossRef] [Google Scholar]
- WANG, Jing, TANG, Jinhui, YANG, Mingkun, et al. Improving OCR-based image captioning by incorporating geometrical relationship. In : Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2021. p. 1306-1315. [Google Scholar]
- CHANDRA, Sushant, SISODIA, Saurav, et GUPTA, Preeti. Optical character recognition-A review. International Research Journal of Engineering and Technology (IRJET), 2020, vol. 7, no 4, p. 3037-3041. [Google Scholar]
- THORAT, Chhanam, BHAT, Aishwarya, SAWANT, Padmaja, et al. A detailed review on text extraction using optical character recognition. ICT Analysis and Applications, 2022, p. 719-728. [Google Scholar]
- SRIVASTAVA, Shubham, VERMA, Ajay, et SHARMA, Shekhar. Optical character recognition techniques: A review. In : 2022 IEEE International Students’ Conference on Electrical, Electronics and Computer Science (SCEECS). IEEE, 2022. p. 1-6. [Google Scholar]
- BANSAL, Shivani, GUPTA, Meenu, et TYAGI, Amit Kumar. A necessary review on optical character recognition (OCR) system for vehicular applications. In : 2020 Second International Conference on Inventive Research in Computing Applications (ICIRCA). IEEE, 2020. p. 918-922. [Google Scholar]
- MOUSSAOUI, Hanae, EL AKKAD, Nabil, et BENSLIMANE, Mohamed. A Brain Tumor Segmentation and Detection Technique Based on Birch and Marker Watershed. SN Computer Science, 2023, vol. 4, no 4, p. 339. [CrossRef] [Google Scholar]
- MOUSSAOUI, Hanae, EL AKKAD, Nabil, et BENSLIMANE, Mohamed. A Review of Video Summarization. Digital Technologies and Applications: Proceedings of ICDTA’23, Fez, Morocco, Volume 1, 2023, p. 516-525. [Google Scholar]
- MOUSSAOUI, Hanae, BENSLIMANE, Mohamed, et EL AKKAD, Nabil. Image segmentation approach based on hybridization between K-means and mask R-CNN. In : WITS 2020: Proceedings of the 6th International Conference on Wireless Technologies, Embedded, and Intelligent Systems. Springer Singapore, 2022. p. 821-830. [Google Scholar]
- MOUSSAOUI, Hanae, EL AKKAD, Nabil, et BENSLIMANE, Mohamed. Moroccan Carpets Classification Based on SVM Classifier and ORB Features. In: Digital Technologies and Applications: Proceedings of ICDTA’22, Fez, Morocco, Volume 2. Cham: Springer International Publishing, 2022. p. 446-455. [CrossRef] [Google Scholar]
- MOUSSAOUI, Hanae, BENSLIMANE, Mohamed, et al. Reinforcement Learning: A review. International Journal of Computing and Digital Systems, 2023, vol. 13, no 1, p. 1-1. [Google Scholar]
- FASKA, Zahra, KHRISSI, Lahbib, HADDOUCH, Khalid, et al. A Powerful and Efficient Method of Image Segmentation Based on Random Forest Algorithm. In: Digital Technologies and Applications: Proceedings of ICDTA 21, Fez, Morocco. Cham: Springer International Publishing, 2021. p. 893-903. [CrossRef] [Google Scholar]
- FASKA, Zahra, KHRISSI, Lahbib, HADDOUCH, Khalid, et al. Random Forest for Semantic Segmentation Using Pre Trained CNN (VGG16) Features. In : Digital Technologies and Applications: Proceedings of ICDTA’23, Fez, Morocco, Volume 2. Cham: Springer Nature Switzerland, 2023. p. 510-520. [CrossRef] [Google Scholar]
- KHRISSI, Lahbib, EL AKKAD, Nabil, SATORI, Hassan, et al. Clustering method and sine cosine algorithm for image segmentation. Evolutionary Intelligence, 2022, p. 1-14. [Google Scholar]
- KHRISSI, Lahbib, EL AKKAD, Nabil, SATORI, Hassan, et al. Simple and efficient clustering approach based on cuckoo search algorithm. In : 2020 Fourth International Conference On Intelligent Computing in Data Sciences (ICDS). IEEE, 2020. p. 1-6. [Google Scholar]
- KHRISSI, Lahbib, EL AKKAD, Nabil, SATORI, Hassan, et al. An Efficient Image Clustering Technique based on Fuzzy C-means and Cuckoo Search Algorithm. International Journal of Advanced Computer Science and Applications, 2021, vol. 12, no 6. [CrossRef] [Google Scholar]
- El Hazzat, S., Merras, M., El Akkad, N., Saaidi, A., Satori, K. Enhancement of sparse 3D reconstruction using a modified match propagation based on particle swarm optimization. Multimedia Tools and Applications, 2019, 78(11), pp. 14251–14276. [CrossRef] [Google Scholar]
- Merras, M., Akkad, N.E., Saaidi, A., Nazih, A.G., Satori, K. Camera Self Calibration with Varying Parameters by an Unknown Three Dimensional Scene Using the Improved Genetic Algorithm. 3D Research, 2015, 6(1), 7 [CrossRef] [Google Scholar]
- LIU, Yuliang, JIN, Lianwen, ZHANG, Shuaitao, et al. Curved scene text detection via transverse and longitudinal sequence connection. Pattern Recognition, 2019, vol. 90, p. 337-345. [Google Scholar]
- NAIEMI, Fatemeh, GHODS, Vahid, et KHALESI, Hassan. A novel pipeline framework for multi oriented scene text image detection and recognition. Expert Systems with Applications, 2021, vol. 170, p. 114549. [CrossRef] [Google Scholar]
- MA, Chixiang, SUN, Lei, ZHONG, Zhuoyao, et al. ReLaText: Exploiting visual relationships for arbitrary-shaped scene text detection with graph convolutional networks. Pattern Recognition, 2021, vol. 111, p. 107684. [CrossRef] [Google Scholar]
- WANG, Huibai et ZHANG, Zhenda. Text detection algorithm based on improved YOLOv3. In : 2019 IEEE 9th International Conference on Electronics Information and Emergency Communication (ICEIEC). IEEE, 2019. p. 147-150. [Google Scholar]
- XU, Yongchao, WANG, Yukang, ZHOU, Wei, et al. Textfield: Learning a deep direction field for irregular scene text detection. IEEE Transactions on Image Processing, 2019, vol. 28, no 11, p. 5566-5579. [Google Scholar]
- WANG, Xiaobing, JIANG, Yingying, LUO, Zhenbo, et al. Arbitrary shape scene text detection with adaptive text region representation. In : Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2019. p. 6449-6458. [Google Scholar]
- WANG, Hao, BAI, Xiang, YANG, Mingkun, et al. Scene text retrieval via joint text detection and similarity learning. In : Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2021. p. 4558-4567. [Google Scholar]
- WANG, Wenhai, XIE, Enze, SONG, Xiaoge, et al. Efficient and accurate arbitrary-shaped text detection with pixel aggregation network. In : Proceedings of the IEEE/CVF international conference on computer vision. 2019. p. 8440-8449. [Google Scholar]
- NEUDECKER, Clemens, BAIERER, Konstantin, GERBER, Mike, et al. A survey of OCR evaluation tools and metrics. In : The 6th International Workshop on Historical Document Imaging and Processing. 2021. p. 13-18. [Google Scholar]
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