Efficient Segmentation Using Attention-Fusion Modules With Dense Predictions by Serdar Erisen

“…Dense predictions are deployed to augment the efficacy of dense-attention-boosting modules and dense-attention-fusion networks, enabling the extraction of global context feature maps in the encoder. …”
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Integration of geospatial techniques and machine learning in land parcel prediction by Nekkanti Haripavan, Subhashish Dey, Chimakurthi Harika Mani Chandana

“…The integration of geospatial techniques and machine learning algorithms has revolutionized our ability to analyze and predict changes in land parcels. …”
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Credit card default prediction using ML and DL techniques by Fazal Wahab, Imran Khan, Sneha Sabada

“…Subsequently, various techniques are employed to preprocess the unprocessed data and visually present the outcomes through the use of exploratory data analysis (EDA). Furthermore, the algorithms are hypertuned to evaluate the enhancement in prediction. …”
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Predicting Court Judgment in Criminal Cases by Text Mining Techniques by Mohammad Farhadishad, Mohammad Kazemifard, Zahra Rezaei

“…Due to high pressures and stress, it may be difficult for them to carefully examine documents and evidence, which leads to more subjective judgments. Legal judgment prediction with artificial intelligence algorithms can benefit judicial bodies, legal experts, and litigants as well as judges. …”
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Ensemble machine learning for predicting academic performance in STEM education by Aklilu Mandefro Messele

“…To tackle these issues, our research focused on developing a predictive model for STEM students using advanced ensemble machine learning algorithms. …”
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Prediction-Based Tip-Over Prevention for Planetary Exploration Rovers by Siddhant Shete, Raúl Domínguez, Ravisankar Selvaraju, Mariela De Lucas Álvarez, Frank Kirchner

“…By leveraging deep learning algorithms, the system evaluates predictions and true measurements in real time to identify potential tip-overs. …”
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Delving into Underwater Image Utility: Benchmark Dataset and Prediction Model by Jiapeng Liu, Yi Liu, Qiuping Jiang

“…On the other hand, based on this newly constructed OD-UIUA dataset, we train a deep UIUA network (DeepUIUA) that can automatically and accurately predict UIUS. To the best of our knowledge, this is the first benchmark dataset for UIUA and also the first model focusing on the specific UIUA problem. …”
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Coal and gas outburst prediction based on data augmentation and neuroevolution. by Wenbing Shi, Ji Huang, Gaoming Yang, Shuzhi Su, Shexiang Jiang

“…This paper proposes a CGO risk prediction method based on data augmentation and a neuroevolution algorithm, denoted as ANEAT. …”
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Multiclass Sparse Bayesian Regression for fMRI-Based Prediction by Vincent Michel, Evelyn Eger, Christine Keribin, Bertrand Thirion

“…However, it relies on a prediction function that is plagued by the curse of dimensionality, as there are far more features (voxels) than samples (images), and dimension reduction is thus a mandatory step. …”
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Impact of stain variation and color normalization for prognostic predictions in pathology by Siyu Lin, Haowen Zhou, Mark Watson, Ramaswamy Govindan, Richard J. Cote, Changhuei Yang

“…This highlights the need to develop an entirely new way to process and collect consistent microscopy images from histologic slides that can be used to both train and allow for the general application of predictive DNN algorithms.…”
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Optimizing Deep Learning Models with Improved BWO for TEC Prediction by Yi Chen, Haijun Liu, Weifeng Shan, Yuan Yao, Lili Xing, Haoran Wang, Kunpeng Zhang

“…The prediction of total ionospheric electron content (TEC) is of great significance for space weather monitoring and wireless communication. …”
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Co-folding, the future of docking – prediction of allosteric and orthosteric ligands by Eva Nittinger, Özge Yoluk, Alessandro Tibo, Gustav Olanders, Christian Tyrchan

“…Recently, computational biology has seen a breakthrough with deep learning algorithms capable of predicting protein structures based on amino acid sequences. …”
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Protein structure prediction via deep learning: an in-depth review by Yajie Meng, Zhuang Zhang, Chang Zhou, Xianfang Tang, Xinrong Hu, Geng Tian, Jialiang Yang, Yuhua Yao, Yuhua Yao, Yuhua Yao

“…The application of deep learning algorithms in protein structure prediction has greatly influenced drug discovery and development. …”
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Prognostic tools or clinical predictions: Which are better in palliative care? by P Stone, V Vickerstaff, A Kalpakidou, C Todd, J Griffiths, V Keeley, K Spencer, P Buckle, D Finlay, R Z Omar

“…PPI was significantly (p<0.001) worse than CPS at predicting which patients would survive for 3 or 6 weeks. …”
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Development of time to event prediction models using federated learning by Rasmus Rask Kragh Jørgensen, Jonas Faartoft Jensen, Tarec El-Galaly, Martin Bøgsted, Rasmus Froberg Brøndum, Mikkel Runason Simonsen, Lasse Hjort Jakobsen

“…Method We propose two methods for training time-to-event prediction models based on distributed data, relying on FL algorithms, for time-to-event prediction models. …”
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Predicting the generalization of computer aided detection (CADe) models for colonoscopy by Joel Shor, Carson McNeil, Yotam Intrator, Joseph R. Ledsam, Hiro-o Yamano, Daisuke Tsurumaru, Hiroki Kayama, Atsushi Hamabe, Koji Ando, Mitsuhiko Ota, Haruei Ogino, Hiroshi Nakase, Kaho Kobayashi, Masaaki Miyo, Eiji Oki, Ichiro Takemasa, Ehud Rivlin, Roman Goldenberg

“…We show that a "Masked Siamese Network" (MSN), trained to predict masked out regions of polyp images without labels, can predict the performance of Computer Aided Detection (CADe) of polyps on colonoscopies, without labels. …”
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Crop Yield Prediction: Data Structure and Ai-Powered Methods by V. K. Kalichkin, K. Yu. Maksimovich, O. A. Aleshchenko, V. V. Aleshchenko

“…(Research purpose) The aim of this study is to analyze data structures and compare machine learning and deep learning algorithms used in used in crop yield prediction. (Materials and methods) Using a convergent approach and applying methods of cognitive and semantic analysis, the authors examined the subject area of artificial intelligence applications in crop yield prediction. …”
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Predicting Quality of Multimedia Experience Using Electrocardiogram and Respiration Signals by Sowmya Vijayakumar, Ronan Flynn, Peter Corcoran, Niall Murray

“…We compare the performances of several machine learning (ML) and deep learning (DL) models in predicting QoE subjective scores from electrocardiograms and respiration signals. …”
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A Hybrid Learning Framework for Enhancing Bridge Damage Prediction by Amal Abdulbaqi Maryoosh, Saeid Pashazadeh, Pedram Salehpour

“…The proposed approach combines pixel-based feature method local binary pattern (LBP) with the mid-level feature bag of visual words (BoVW) for feature extraction, followed by the Apriori algorithm for dimensionality reduction and optimal feature selection. …”
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Composite Noise Reduction Method for Internal Leakage Acoustic Emission Signal of Safety Valve Based on IWTD-IVMD Algorithm by Shuxun Li, Xiaoqi Meng, Jianjun Hou, Kang Yuan, Xiaoya Wen

“…Therefore, the IWTD-IVMD composite noise reduction method can extract more main features out of the measured spring full-open safety valve internal leakage acoustic emission signals, and has a good noise reduction effect. …”
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