Fast and accurate deep learning scans for signatures of natural selection in genomes using FASTER-NN by Sjoerd van den Belt, Nikolaos Alachiotis

“…Abstract Deep learning classification models based on Convolutional Neural Networks (CNNs) are increasingly used in population genetic inference for detecting signatures of natural selection. …”
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Improvement of IRI Global TEC Maps by Deep Learning Based on Conditional Generative Adversarial Networks by Eun‐Young Ji, Yong‐Jae Moon, Eunsu Park

“…Abstract In this study, we make a model, which is called DeepIRI, to generate improved International Reference Ionosphere (IRI) total electron content (TEC) maps by deep learning based on conditional Generative Adversarial Networks. …”
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DeepAptamer: Advancing high-affinity aptamer discovery with a hybrid deep learning model by Xin Yang, Chi Ho Chan, Shanshan Yao, Hang Yin Chu, Minchuan Lyu, Ziqi Chen, Huan Xiao, Yuan Ma, Sifan Yu, Fangfei Li, Jin Liu, Luyao Wang, Zongkang Zhang, Bao-Ting Zhang, Lu Zhang, Aiping Lu, Yaofeng Wang, Ge Zhang, Yuanyuan Yu

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Exploring the Preprocessing of a Time-Series Healthcare Administrative Dataset on Deep Learning to Improve Prediction by Faezehsadat Shahidi, M. Ethan Macdonald, Dallas Seitz, Rebecca Barry, Geoffrey Messier

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Identification of bald patches in degraded alpine meadows by UAV-based remote sensing and deep learning by Lu Wang, Lulu Cui, Zihan Song, Min Zheng, Chengyi Li, Xilai Li

Subjects: “…deep learning…”
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Classification and Analysis of <em>Agaricus bisporus</em> Diseases with Pre-Trained Deep Learning Models by Umit Albayrak, Adem Golcuk, Sinan Aktas, Ugur Coruh, Sakir Tasdemir, Omer Kaan Baykan

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Image-Based Arabic Sign Language Recognition System Using Transfer Deep Learning Models by Qanita Bani Baker, Nour Alqudah, Tibra Alsmadi, Rasha Awawdeh

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Research on the Application of Deep Learning Technology Oriented to the Construction and Innovation of Smart City Image Cognition by Dan Shi, Lixin Song

“…With the advent of the era of big data and the development of Internet technology, there are more and more quantitative research results on smart city image cognition with the help of big data and deep learning technology. It will be a feasible way to apply it to urban image research. …”
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A comparative analysis of the health monitoring process using deep learning methods for brain tumour by N. Manjunathan, N. Gomathi

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Advancements in Machine Learning and Deep Learning Techniques for Crop Yield Prediction: A Comprehensive Review by V. Ramesh and P. Kumaresan

Subjects: “…crop yield prediction, machine learning, deep learning, artificial neural networks, optimization algorithms…”
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Depression Detection in Social Media: A Comprehensive Review of Machine Learning and Deep Learning Techniques by Waleed Bin Tahir, Shah Khalid, Sulaiman Almutairi, Mohammed Abohashrh, Sufyan Ali Memon, Jawad Khan

Subjects: “…Deep learning…”
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Automatic Aortic Valve Extraction Using Deep Learning with Contrast-Enhanced Cardiac CT Images by Soichiro Inomata, Takaaki Yoshimura, Minghui Tang, Shota Ichikawa, Hiroyuki Sugimori

Subjects: “…deep learning…”
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IMPROVING PREDICTION ACCURACY OF DEEP LEARNING FOR BRAIN CANCER DIAGNOSIS USING POLYAK-RUPPERT OPTIMIZATION by M Muthulekshmi, Azath Mubarakali, Y M Blessy

Subjects: “…computer-aided diagnosis, brain cancer, deep learning, convolutional neural network, polyak ruppert optimization…”
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A security data detection and management method in digital library network based on deep learning by Diyin Zhu, Yihang Wei, Jiali Cai, Jingwen Wang, Zhongshan Chen

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Threat analysis and defense methods of deep-learning-based data theft in data sandbox mode by Hezhong PAN, Peiyi HAN, Xiayu XIANG, Shaoming DUAN, Rongfei ZHUANG, Chuanyi LIU

“…The threat model of deep-learning-based data theft in data sandbox model was analyzed in detail, and the degree of damage and distinguishing characteristics of this attack were quantitatively evaluated both in the data processing stage and the model training stage.Aiming at the attack in the data processing stage, a data leakage prevention method based on model pruning was proposed to reduce the amount of data leakage while ensuring the availability of the original model.Aiming at the attack in model training stage, an attack detection method based on model parameter analysis was proposed to intercept malicious models and prevent data leakage.These two methods do not need to modify or encrypt data, and do not need to manually analyze the training code of deep learning model, so they can be better applied to data theft defense in data sandbox mode.Experimental evaluation shows that the defense method based on model pruning can reduce 73% of data leakage, and the detection method based on model parameter analysis can effectively identify more than 95% of attacks.…”
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Deep Learning Based Dual Channel Banana Grading System Using Convolution Neural Network by Raghavendra S, Souvik Ganguli, P. Thirumarai Selvan, Mitali Madhusmita Nayak, Sushovan Chaudhury, Randell U. Espina, Isaac Ofori

“…Deep learning has recently been hailed as the most advanced computer vision technology for image classification. …”
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Deep Learning based Individual Cattle Face Recognition using Data Augmentation and Transfer Learning by Caner Koç, Kamil Ekinci, Ömer Ertuğrul, Dilara Gerdan Koc, Havva Eylem Polat

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Cardiac MR image reconstruction using cascaded hybrid dual domain deep learning framework. by Madiha Arshad, Faisal Najeeb, Rameesha Khawaja, Amna Ammar, Kashif Amjad, Hammad Omer

“…Deep learning-based MR image reconstruction methods are divided into two categories: (a) single domain methods (image domain learning and k-space domain learning) and (b) cross/dual domain methods. …”
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Prediction of the SYM‐H Index Using a Bayesian Deep Learning Method With Uncertainty Quantification by Yasser Abduallah, Khalid A. Alobaid, Jason T. L. Wang, Haimin Wang, Vania K. Jordanova, Vasyl Yurchyshyn, Huseyin Cavus, Ju Jing

“…Abstract We propose a novel deep learning framework, named SYMHnet, which employs a graph neural network and a bidirectional long short‐term memory network to cooperatively learn patterns from solar wind and interplanetary magnetic field parameters for short‐term forecasts of the SYM‐H index based on 1‐ and 5‐min resolution data. …”
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DeepBase: A Deep Learning-based Daily Baseflow Dataset across the United States by Parnian Ghaneei, Hamid Moradkhani

“…This study focuses on estimating baseflow using deep learning algorithms that enhance the estimation capabilities in both gauged and ungauged basins. …”
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