Application of artificial intelligence in insect pest identification - A review by Sourav Chakrabarty, Chandan Kumar Deb, Sudeep Marwaha, Md. Ashraful Haque, Deeba Kamil, Raju Bheemanahalli, Pathour Rajendra Shashank

“…These methods have revolutionized insect identification by analyzing large databases of insect images and identifying distinct patterns and features linked to different species. AI-powered systems can improve insect pest identification by utilizing other data modalities. …”
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ResWLI: a new method to retrieve water levels in coastal zones by integrating optical remote sensing and deep learning by Nan Xu, Huichao Xin, Jiarui Wu, Jiaqi Yao, He Ren, Han-Su Zhang, Hao Xu, Hong Luan, Dong Xu, Yongze Song

“…Although two stations had RMSE values exceeding 0.20 m, the ResWLI proved to be a reliable and accurate method for water level estimation across different tide conditions. Future works could further explore other sources of satellite imagery for high-frequent monitoring of water level changes on a larger scale, potentially on a global scale. …”
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PSDA: Pyramid Spatial Deformable Aggregation for Building Segmentation in Multiview Remote Sensing Images by Xuejun Huang, Yi Wan, Yongjun Zhang, Xinyi Liu, Bin Zhang, Yameng Wang, Haoyu Guo, Yingying Pei, Zhonghua Hu

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AI-Powered Dental Forensics in Transforming Age Estimation Techniques: A Narrative Review by Parul Khare, Kalyani Bhargava, M Siddharth, Deepak Bhargava, Anoushka Chauhan

“…This review highlights how combining AI with different imaging techniques can enhance accuracy, reduce human error and address population-specific variations in forensic age estimation.…”
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Assessment of Scientific Creative-Potential by Near-Infrared Spectroscopy Using Brain-Network-Based Deep-Fuzzy Classifier by Sayantani Ghosh, Amit Konar, Atulya K. Nagar

“…Hence, the proposed approach may prove effective for recruiting individuals with varying degrees of scientific creativity across different research sectors.…”
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BCSnet: A U-Net-Based Model for Segmentation of Brain Cells in Trypan Blue Images by Aleksei A. Kudryavtsev, Ivan V. Simkin, Maksim A. Dragun, Olga P. Alexandrova, Ivan P. Malashin, Denis A. Sukhanov, Vladimir A. Nelyub, Aleksei S. Borodulin, Stanislav O. Yurchenko, Vadim S. Tynchenko

“…This method requires a lot of time and effort associated with the need for manual cell counting and qualification in histology to detect visual differences between alive neuron cells and non-alive ones. …”
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Neural network pruning based on channel attention mechanism by Jianqiang Hu, Yang Liu, Keshou Wu

“…However, most of the existing methods ignore the differences in the contributions of the output feature maps. …”
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Capsule network based analysis of histopathological images of oral squamous cell carcinoma by Santisudha Panigrahi, Jayshankar Das, Tripti Swarnkar

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Faster R-CNN model for target recognition and diagnosis of scapular fractures by Qiong Fang, Anhong Jiang, Meimei Liu, Sen Zhao

“…Objective: This study aims to establish a diagnostic model for scapular fractures using a convolutional neural network (CNN) and to discuss the clinical advantages of this model in diagnosing such complex conditions. …”
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Unraveling Parkinson's disease motor subtypes: A deep learning approach based on spatiotemporal dynamics of EEG microstates by Lin Meng, Deyu Wang, Jun Ma, Yu Shi, Hongbo Zhao, Yanlin Wang, Qingqing Shi, Xiaodong Zhu, Dong Ming

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Fault diagnosis method for rigid guides in vertical shaft hoisting systems by WANG Jianfeng, JIN Yuanzhi, ZHANG Yong, WANG Yongzhen, HE Jiacong

“…The network extracted multi-scale features through parallel multi-scale convolutions, enhancing its ability to perceive signal features at different scales. …”
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Automated orofacial virtual patient creation using two cohorts of MSCT vs. CBCT scans by Thanatchaporn Jindanil, Oana-Elena Burlacu-Vatamanu, Benedetta Baldini, Joeri Meyns, Jeroen Meewis, Rocharles Cavalcante Fontenele, Maria Cadenas de Llano Perula, Reinhilde Jacobs

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Constructing an artificial intelligence-assisted system for the assessment of gastroesophageal valve function based on the hill classification (with video) by Jian Chen, Ganhong Wang, Kaijian Xia, Zhenni Wang, Luojie Liu, Xiaodan Xu

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A Deep Learning Approach to Evaluating SISO-OFDM Channel Equalization by Saja S Hanoon, Hasan F Khazal, Thamer M Jamel

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PermQRDroid: Android malware detection with novel attention layered mini-ResNet architecture over effective permission information image by Kazım Kılıç, İbrahim Alper Doğru, Sinan Toklu

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Algorithm for pixel-level concrete pavement crack segmentation based on an improved U-Net model by Zixuan Zhang, Yike He, Di Hu, Qiang Jin, Manxu Zhou, Zongwei Liu, Hongli Chen, He Wang, Xinchen Xiang

“…Abstract Cracks that occur in concrete surfaces are numerous and diverse, and different cracks will affect road safety in different degrees. …”
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Exploring Generative Adversarial Network-Based Augmentation of Magnetic Resonance Brain Tumor Images by Mahnoor Mahnoor, Oona Rainio, Riku Klén

“…Background: A generative adversarial network (GAN) has gained popularity as a data augmentation technique in the medical field due to its efficiency in creating synthetic data for different machine learning models. In particular, the earlier literature suggests that the classification accuracy of a convolutional neural network (CNN) used for detecting brain tumors in magnetic resonance imaging (MRI) images increases when GAN-generated images are included in the training data together with the original images. …”
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An ensemble deep learning model for author identification through multiple features by Yuan Zhang

“…Our approach enhances generalization to a great extent by combining a wide range of writing styles representations such as statistical features, TF-IDF vectors, and Word2Vec embeddings. The different sets of features are fed through separate Convolutional Neural Networks (CNN) so that the specific stylistic features can be extracted. …”
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Evolution of deep learning tooth segmentation from CT/CBCT images: a systematic review and meta-analysis by Wai Ying Kot, Sum Yin Au Yeung, Yin Yan Leung, Pui Hang Leung, Wei-fa Yang

“…Various deep learning algorithms were categorized according to the backbone network, encompassing single-stage convolutional models, convolutional models with U-Net architecture, Transformer models, convolutional models with attention mechanisms, and combinations of multiple models. …”
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A Comparative Analysis of Deep Learning-Based Segmentation Techniques for Terrain Classification in Aerial Imagery by Martina Formichini, Carlo Alberto Avizzano

“…Nevertheless, most of these networks were designed to perform in different scenarios, such as autonomous driving and medical imaging. …”
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