Maize yield estimation in Northeast China’s black soil region using a deep learning model with attention mechanism and remote sensing by Xingke Li, Yunfeng Lyu, Bingxue Zhu, Lushi Liu, Kaishan Song

“…In the predictions for the most recent year, the model demonstrated high accuracy (R² = 0.896, RMSE = 908.33 kg/ha) and exhibited strong robustness in both earlier years and during extreme climatic events. …”
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The classification of EMG signals using machine learning for the construction of a silent speech interface. by Chandrashekhar, V.

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An efficient graph attention framework enhances bladder cancer prediction by Taghreed S. Ibrahim, M. S. Saraya, Ahmed I. Saleh, Asmaa H. Rabie

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Benchmarking the NXP i.MX8M+ neural processing unit: smart parking case study by Edgar Chaves-González, Luis G. León-Vega

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A comprehensive survey on RGB-D-based human action recognition: algorithms, datasets, and popular applications by Yumin Zhang, Yanyong Wang

“…Abstract Due to the rapid advances in computer vision and deep learning, human action recognition has become one of the most important representative tasks for video understanding. …”
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A study on Chinese language Cross-Modal pedestrian image information retrieval by Yan Xie, Jian Qu

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Explainable AI for Alzheimer Detection: A Review of Current Methods and Applications by Fatima Hasan Saif, Mohamed Nasser Al-Andoli, Wan Mohd Yaakob Wan Bejuri

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The Comparison of Activation Functions in Feature Extraction Layer using Sharpen Filter by Oktavia Citra Resmi Rachmawati, Ali Ridho Barakbah, Tita Karlita

“…The findings revealed that ReLU consistently outperformed other activation functions by achieving the lowest MSE values, making it the most effective choice for feature extraction tasks using sharpening filters. …”
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A Proposed Method for Deep Learning-Based Automatic Tracking with Minimal Training Data for Sports Biomechanics Research by Daichi Yamashita, Minoru Matsumoto, Takeo Matsubayashi

“…These annotated frames are subsequently used to train a deep learning model that leverages a pre-trained VGG16 network as its backbone and incorporates an additional convolutional head. Feature maps extracted from three intermediate layers of VGG16 are processed by the head network to generate a probability map, highlighting the most likely locations of the key points. …”
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A Method of Simplified Synthetic Objects Creation for Detection of Underwater Objects from Remote Sensing Data Using YOLO Networks by Daniel Klukowski, Jacek Lubczonek, Pawel Adamski

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A Global Deep Learning Perspective on Australia-Wide Monthly Precipitation Prediction by Luyi Shen, Guoqi Qian, Antoinette Tordesillas

“…This method ranks cumulative rainfall levels, enabling focused analysis on areas most affected by extreme weather events. Our assessment from April 2021 to March 2022 highlights the model’s proficiency in identifying significant rainfall, especially in flood-impacted locations. …”
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IEDSFAN: information enhancement and dynamic-static fusion attention network for traffic flow forecasting by Lianfei Yu, Ziling Wang, Wenxi Yang, Zhijian Qu, Chongguang Ren

“…However, traffic flow forecasting still faces serious challenges. Most of the existing traffic flow forecasting methods are static graph convolutional networks based on prior knowledge, ignoring the special spatial–temporal dynamics of spatial–temporal data. …”
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Segmentation of dermatoscopic images of skin lesions. Comparison of methods by A. F. Smalyuk, M. S. Dzeshka, I. D. Kupchykava

“…Segmentation is necessary as the first stage of most methods of computer diagnostics of malignancy of neoplasms. …”
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Fine-Tuning-Based Transfer Learning for Building Extraction from Off-Nadir Remote Sensing Images by Bipul Neupane, Jagannath Aryal, Abbas Rajabifard

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<p><strong>Deep-learning techniques for symptoms' detection of <em>Aculops lycopersici</em></strong> <strong>(Acari: Eriophyidae) and <em>Tuta absoluta</em></strong> (<strong>Lepid... by Alireza Shabani Nezhad, Maryam Aleosfoor

“… Accurate pest detection is the most fundamental requirement in the management of damage-causing factors. …”
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Breast cancer image classification by using HCNN and LeNet5 by Pramoda Patro, Shaik Honey Fathima, R. Harikishore, Aditya Kumar Sahu

“…Breast cancer (BC) is one of the most common cancers in women; the death rate is high and holds the second position next to lung cancer. …”
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A New Analysis of Web Customer Service Text Classification of Alexa Virtual Assistant Commands Using a Deep Learning Model by Seidakhmet Nurpatsha

“…The experimental results demonstrate that the CNN model achieves the highest recall (0.86) and accuracy (0.88), making it the most effective model for classifying Alexa commands. …”
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Shifted Hexpo activation function: An improved vanishing gradient mitigation activation function for disease classification by Joseph Otoo, Suleman Nasiru, Irene Dekomwine Angbing

“…Additionally, Grad-CAM visualizations highlight SHexpo’s capability to enhance interpretability by localizing the most relevant image regions contributing to model predictions. …”
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Graph-Based Feature Crossing to Enhance Recommender Systems by Congyu Cai, Hong Chen, Yunxuan Liu, Daoquan Chen, Xiuze Zhou, Yuanguo Lin

“…In recommendation tasks, most existing models that learn users’ preferences from user–item interactions ignore the relationships between items. …”
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A Hybrid CNN-LSTM Approach for Muscle Artifact Removal from EEG Using Additional EMG Signal Recording by Marcin Kołodziej, Marcin Jurczak, Andrzej Majkowski, Andrzej Rysz, Bartosz Świderski

“…Although numerous algorithms have been proposed, most rely solely on EEG data. In this study, we introduce a novel approach utilizing a hybrid convolutional neural network–long short-term memory (CNN-LSTM) architecture alongside simultaneous recording of facial and neck EMG signals. …”
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