Influence of cognitive networks and task performance on fMRI-based state classification using DNN models by Murat Kucukosmanoglu, Javier O. Garcia, Justin Brooks, Kanika Bansal

“…Here, we employ two different and complementary DNN models, a one-dimensional convolutional neural network (1D-CNN) and a bidirectional long short-term memory network (BiLSTM), to classify cognitive task states from fMRI data, focusing on the cognitive underpinnings of the classification. …”
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AI-Assisted identification of sex-specific patterns in diabetic retinopathy using retinal fundus images. by Parsa Delavari, Gulcenur Ozturan, Eduardo V Navajas, Ozgur Yilmaz, Ipek Oruc

“…Here we examine whether DR manifests differently in male and female patients, using a dataset of retinal images and leveraging convolutional neural networks (CNN) integrated with explainable artificial intelligence (AI) techniques. …”
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Technical note: Impact of tissue section thickness on accuracy of cell classification with a deep learning network by Ida Skovgaard Christiansen, Rasmus Hartvig, Thomas Hartvig Lindkær Jensen

“…Method: From HE-stained digitized sections of liver cut manually at 5 thicknesses and on an automated microtome (DS), hepatocytes and non-hepatocytes were manually annotated and loaded into a DL convolutional neural network (ResNet). The network was trained at different settings to identify the thickness with optimal relation between number of training cells and validation accuracy. …”
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A dual-branch deep learning model based on fNIRS for assessing 3D visual fatigue by Yan Wu, Yan Wu, Yan Wu, TianQi Mu, SongNan Qu, XiuJun Li, XiuJun Li, XiuJun Li, Qi Li, Qi Li, Qi Li

“…Given the time-series nature of fNIRS data and the variability of fatigue responses across different brain regions, a dual-branch convolutional network was constructed to separately extract temporal and spatial features. …”
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Digital Biomarkers for Parkinson Disease: Bibliometric Analysis and a Scoping Review of Deep Learning for Freezing of Gait by Wenhao Qi, Shiying Shen, Chaoqun dong, Mengjiao Zhao, Shuaiqi Zang, Xiaohong Zhu, Jiaqi Li, Bin Wang, Yankai Shi, Yongze Dong, Huajuan Shen, Junling Kang, Xiaodong Lu, Guowei Jiang, Jingsong Du, Eryi Shu, Qingbo Zhou, Jinghua Wang, Shihua Cao

“…In addition, 31 (78%) studies indicated that the best models were primarily convolutional neural networks or convolutional neural networks–based architectures. …”
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A novel method for soil organic carbon prediction using integrated ‘ground-air-space’ multimodal remote sensing data by Yilin Bao, Xiangtian Meng, Huanjun Liu, Mengyuan Xu, Mingchang Wang

“…To address this challenge, we propose an innovative multimodal remote sensing data integration framework, ResoCroS-Net, which integrates ground (soil samples), air (unmanned aerial vehicle (UAV) images), and space (satellite images) data, realized effective integration of multimodal data at different resolutions, with particular innovations in hierarchical design and data-processing logic. …”
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Needle detection and localisation for robot‐assisted subretinal injection using deep learning by Mingchuan Zhou, Xiangyu Guo, Matthias Grimm, Elias Lochner, Zhongliang Jiang, Abouzar Eslami, Juan Ye, Nassir Navab, Alois Knoll, Mohammad Ali Nasseri

“…In this paper we demonstrate a robust framework for needle detection and localisation in robot‐assisted subretinal injection using microscope‐integrated Optical Coherence Tomography with deep learning. Five convolutional neural networks with different architectures were evaluated. …”
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Accurate, automated classification of radiographic knee osteoarthritis severity using a novel method of deep learning: Plug-in modules by Do Weon Lee, Dae Seok Song, Hyuk-Soo Han, Du Hyun Ro

“…The final deep learning model was designed through an ensemble of four different PIMs. Results The accuracy was the lowest for KL grade 1 (43%) and the highest for KL grade 4 (96%). …”
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Application of CycleGAN-based low-light image enhancement algorithm in foreign object detection on belt conveyors in underground mines by Anxin Zhao, Qiuhong Zheng, Liang Li

“…Second, a lighting enhancement module is designed to achieve global brightness equalization and reduce contrast differences between different regions. Finally, a dynamic effective self-attention aggregation module is designed to suppress the generation of noise and artifacts. …”
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Keywords, morpheme parsing and syntactic trees: features for text complexity assessment by Dmitry A. Morozov, Ivan A. Smal, Timur A. Garipov, Anna V. Glazkova

“…We conducted a comparison using four different machine learning algorithms and four annotated Russian-language text corpora. …”
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Diverse behavior clustering of students on campus with macroscopic attention by Wanghu Chen, Zongjuan Wu, Siqi Zeng, Hongle Guo, Jing Li

“…Since cognitive psychology believes that all behaviors can be regarded as attention to different objects, this paper proposes an analysis framework based on Macroscopic Attention (MA) to characterize the diverse behavior of individuals. …”
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LFEN: A language feature enhanced network for scene text recognition by Hui Chen, Runming Jiang, Fang Hu, Min Chen, Yin Zhang

“…Furthermore, by incorporating the intrinsic semantic relationships of text content, this paper employs a sequence-to-sequence (Seq2Seq) model based on convolutional neural networks for text correction. Through the integration of language information, different feature embeddings, and global residual connections, the paper provides a robust solution for text correction in scene text recognition. …”
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Ubiquitous UWB Ranging Error Mitigation With Application to Infrastructure-Free Cooperative Positioning by Maija Makela, Martta-Kaisa Olkkonen, Martti Kirkko-Jaakkola, Toni Hammarberg, Tuomo Malkamaki, Jesperi Rantanen, Sanna Kaasalainen

“…This ranging error can be corrected with machine learning (ML) methods, such as convolutional neural networks (CNNs). However, these ML models often generalize poorly between different environments. …”
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Multi-Modality Sheep Face Recognition Based on Deep Learning by Sheng Liao, Yan Shu, Fang Tian, Yong Zhou, Guoliang Li, Cheng Zhang, Chao Yao, Zike Wang, Longjie Che

“…To address the challenge of recognizing sheep faces of the same type, which exhibit significant similarities and varying performance of RGB images under different lighting conditions and angles, this paper proposes a dual-branch multi-modal sheep face recognition model based on the ResNet18 architecture. …”
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The Effect of Input Length on Prediction Accuracy in Short-Term Multi-Step Electricity Load Forecasting: A CNN-LSTM Approach by Seyda Ozdemir, Yakup Demir, Ozal Yildirim

“…The model is tested on 12 different configurations with symmetrically increasing input lengths, including weather data. …”
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Deep learning HRNet FCN for blood vessel identification in laparoscopic pancreatic surgery by Jile Shi, Ruohan Cui, Zhihong Wang, Qi Yan, Lu Ping, Hu Zhou, Junyi Gao, Chihua Fang, Xianlin Han, Surong Hua, Wenming Wu

“…By combining datasets from LDP and Whipple procedures, the model showed strong generalization across different surgical contexts and achieved real-time processing speeds of 11 frames per second during surgery process. …”
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A Novel Dual-Stream Attention-Based Hybrid Network for Solar Power Forecasting by Rafiq Asghar, Michele Quercio, Lorenzo Sabino, Assia Mahrouch, Francesco Riganti Fulginei

“…The proposed model’s performance is thoroughly assessed by a series of experiments that include various window sizes, four seasons, and different weather conditions. Subsequently, the predictive accuracy of the developed model is compared with three single and five hybrid deep learning models. …”
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Development of a Mobile-Based Application for Classifying Caladium Plants Using the CNN Algorithm by Rudy Chandra, Tegar Arifin Prasetyo, Heni Ernita Lumbangaol, Veny Siahaan, Johan Immanuel Sianipar

“…However, difficulties in recognizing the type of Caladium often occur because of the similarities in shape, pattern, and color of the leaves between the different kinds of Caladium. To overcome this problem, research will use machine learning with the Convolutional Neural Network (CNN) algorithm to build a mobile application that can accurately classify four types of Caladiums. …”
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A Review on Image Enhancement and Restoration Techniques for Underwater Optical Imaging Applications by N. Deluxni, Pradeep Sudhakaran, Kitmo, Mouhamadou Falilou Ndiaye

“…Various UIE techniques are studied for different data sets, and applications. However, the selection of suitable method for particular applications among available techniques is still a challenging task. …”
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Short Term Photovoltaic Power Combination Prediction Method Based on Similar Day Selection and Data Reconstruction by Qingbin CHEN, Genghuang YANG, Liqing GENG, Juan SU, Jingsheng SUN

“…Through practical examples, it has been verified that under different weather conditions, the overall prediction error of the model is the smallest, which can effectively improve the prediction accuracy.…”
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