TFTformer: A novel transformer based model for short-term load forecasting by Ahmad Ahmad, Xun Xiao, Huadong Mo, Daoyi Dong

“…Additionally, a Temporal Convolutional Network is integrated within the Transformer’s encoder, employing causal convolutions and dilation to adapt to the sequential nature of data with an expanded receptive field. …”
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Relation extraction based on CNN and Bi-LSTM by Xiaobin ZHANG, Fucai CHEN, Ruiyang HUANG

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Does Using Artificial Intelligence in Citizen Science Support Volunteers’ Learning? An Experimental Study in Ornithology by Khrystyna Pankiv, Laure Kloetzer

“…The Cornell Lab has also developed a mobile application, Merlin, which uses a deep convolutional neural network to help users automatically identify bird species from photos, sounds (converted to spectrograms), or descriptions. …”
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FruitsMultiNet: A deep neural network approach to identify fruits through multi-scale feature fusion using mobile interface by Tasauf Mim, Md Mahbubur Rahman, Jahanur Biswas, Ahmad Shafkat, Khandaker Mohammad Mohi Uddin

“…A reliable fruit classification system during harvest and post-harvest phases can minimize time, cost, and human error while modernizing the processes of sorting, labeling, and packaging. …”
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3D Anisotropic Asymmetric Pyramid (AAP-Net) Network Model for Brain Metastases Segmentation on Multi-Sequence MRI by Omar Farghaly, Priya Deshpande

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Deep learning-based debris flow hazard detection and recognition system: a case study by Fei Wu, Jianlin Zhang, Dunlong Liu, Andreas Maier, Vincent Christlein

“…So far, video cameras are used as a passive tool for post inspection and not as an active role for debris flow monitoring and early warning. …”
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Deep Learning Models for Detection and Severity Assessment of Cercospora Leaf Spot (<i>Cercospora capsici</i>) in Chili Peppers Under Natural Conditions by Douglas Vieira Leite, Alisson Vasconcelos de Brito, Gregorio Guirada Faccioli, Gustavo Haddad Souza Vieira

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Monte-Carlo Modelling For Evaluation Of Two Different Calculation Algorithms by Baljeet Seniwal, Telma C. F. Fonseca, Ranjit Singh

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Chaotic moving video quality enhancement based on deep in-loop filtering by Tong Tang, Yi Yang, Dapeng Wu, Ruyan Wang, Zhidu Li

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Multi-granularity Android malware fast detection based on opcode by Xuetao ZHANG, Meng SUN, Jinshuang WANG

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Protective Effects of Withania Somnifera Against Cisplatin-Induced Acute Kidney Injury in Rats: A Histomorphometric Analysis by Aaqiba Rasheed, Nadia Younus, Nausheen Jamshed, Lubna Faisal, Naureen Waseem, Rana Muhammad Zeeshan, Omar Shamim

“…There was a decrease in the mean Proximal convoluted tubule count and Proximal convoluted tubule cell count of Cisplatin treated group.  …”
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SapotaNet: Paving the Way for Efficient Deep Learning with Lightweight Network Architecture by Anita Bhatt, Maulin Joshi

“…However, having a short post-harvest life and a lack of human resources result in high post-harvest losses in the case of Sapota fruit production. …”
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A fully-automated technique for cartilage morphometry in knees with severe radiographic osteoarthritis – Method development and validation by Wolfgang Wirth, Felix Eckstein

“…Objective: Denuded areas of subchondral bone (dAB) pose a challenge for fully automated segmentation of articular cartilage and subchondral bone in knees with severe radiographic osteoarthritis using convolutional neural networks (CNNs). Here we propose an automated post-processing relying on a selection-based multi-atlas registration for reconstructing the total area of subchondral bone (tAB) to overcome this issue. …”
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High sensitivity in spontaneous intracranial hemorrhage detection from emergency head CT scans using ensemble-learning approach by Juuso Takala, Heikki Peura, Riku Pirinen, Katri Väätäinen, Sergei Terjajev, Ziyuan Lin, Rahul Raj, Miikka Korja

“…The DL solution included four base convolutional neural networks (CNNs), which were trained using 300 head CT scans. …”
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An Approach of Intelligent Compound Fault Diagnosis of Rolling Bearing based on MWT and CNN by Han Tao, Yuan Jianhu, Tang Jian, An Lizhou

“…An approach to intelligent compound fault diagnosis of rolling bearing using multi- wavelet transform（ MWT） and convolution neural network（ CNN） was proposed. According to this approach,the vibration signals of rolling bearing are analyzed by using MWT of removed post processing,and the corresponding multi- wavelet coefficient branches are obtained. …”
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Machine vision-based automatic fruit quality detection and grading by Amna, Muhammad Waqar AKRAM, Guiqiang LI, Muhammad Zuhaib AKRAM, Muhammad FAHEEM, Muhammad Mubashar OMAR, Muhammad Ghulman HASSAN

“…Artificial intelligence-based automatic systems can reduce time, human error and post-harvest operations. By using such systems, food items can be successfully classified and graded based on defects. …”
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Working-memory load decoding model inspired by brain cognition based on cross-frequency coupling by Jing Zhang, Tingyi Tan, Yuhao Jiang, Congming Tan, Liangliang Hu, Daowen Xiong, Yikang Ding, Guowei Huang, Junjie Qin, Yin Tian

“…Drawing inspiration from the role of cross-frequency coupling in the hippocampal region, which plays a crucial role in advanced cognitive processes such as working memory, this study proposes a Multi-Band Multi-Scale Hybrid Sinc Convolutional Neural Network (MBSincNex). This model integrates multi-frequency and multi-scale Sinc convolution to facilitate time-frequency conversion and extract time-frequency information from multiple rhythms and regions of the EEG data with the aim of effectively model the cross-frequency coupling across different cognitive domains. …”
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A Predictive Method for Unplanned Postoperative Readmission Risk Based on Heterogeneous Data by Kai YU, Xiaofeng DONG, Zhenming YUAN, Zhaojian CUI, Weibin LUO

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Time Series-Based Fault Detection and Classification in IEEE 9-Bus Transmission Lines Using Deep Learning by Somchat Jiriwibhakorn, Shazia Kanwal

“…This paper explores a time series-based deep learning technique for fault detection and classification in the IEEE 9-bus system. Post asymmetrical fault current and voltage time series data have been used to train a convolutional neural network (CNN), representing normal and faulty conditions, with convolutional and ReLU layers. …”
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Deep learning-based video analysis for automatically detecting penetration and aspiration in videofluoroscopic swallowing study by Soyoung Kwak, Jeoung Kun Kim, Jun Sung Moon, Gun Woo Lee, Sungho Kim, Min Cheol Chang

“…The model was trained with a convolutional neural network architecture, incorporating techniques to address class imbalance and optimize performance. …”
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