{"product_id":"engineering-applications-of-neural-networks-9783031961953","title":"Engineering Applications of Neural Networks","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e.- A Real-Time Human Action Recognition Model for Assisted Living.\u003c\/p\u003e\u003cp\u003e.- A Survey of Federated Learning-Based Intrusion Detection Methods in Medical IoT\u003c\/p\u003e\u003cp\u003e.- AI-based automatic counting and classification of aedes mosquito eggs in field traps.\u003c\/p\u003e\u003cp\u003e.- An Empirical Review of Uncertainty Estimation for Quality Control in CAD Model Segmentation.\u003c\/p\u003e\u003cp\u003e.- Brain Inspired Learning for Neural Networks.\u003c\/p\u003e\u003cp\u003e.- Comparative Analysis of Machine Learning Techniques for Chronic Kidney Disease Prediction Efficiency.\u003c\/p\u003e\u003cp\u003e.- Detecting Anomalous Self-Citations using Citation Network Analysis and LLMs.\u003c\/p\u003e\u003cp\u003e.- Early Detection of Voice Pathology from Cry Analysis Using Non-Interpretable Features and Parallel 1D CNN.\u003c\/p\u003e\u003cp\u003e.- Easy, Fast and Reliable Modulo and Linear Congruential Generator Approximation with Artificial Neural Networks.\u003c\/p\u003e\u003cp\u003e.- EEG-based Hybrid Emotion Recognition Model with Statistical-Wavelet Features and Modality-Agnostic Loss.\u003c\/p\u003e\u003cp\u003e.- ESN with delayed inputs to model industrial processes.\u003c\/p\u003e\u003cp\u003e.- Exploring Knowledge Distillation for Model Compression in Edge Environments.\u003c\/p\u003e\u003cp\u003e.- Exploring Various Sequential Learning Methods  for Deformation History Modeling.\u003c\/p\u003e\u003cp\u003e.- FusionNet:Leveraging Dual Speech Separation Networks for Enhanced Multi-Speaker Isolation.\u003c\/p\u003e\u003cp\u003e.- Hybrid Deep Learning and Gradient Boosting for Superior Sentiment Analysis: A Comparative Study.\u003c\/p\u003e\u003cp\u003e.- Implementing Hybrid Tsetlin Machine and Q-Learning for Solving the Job Shop Scheduling.\u003c\/p\u003e\u003cp\u003e.- Maximum Interstory Drift Ratio (MIDR) equations for R\/C buildings using machine learning procedures.\u003c\/p\u003e\u003cp\u003e.- MRI-Based Brain Tumor Classification Using Ensemble CNN, VGG16, and ResNet50 Model.\u003c\/p\u003e\u003cp\u003e.- Needle-in-the-Haystack Testing LLMs with a Complex Reasoning Task.\u003c\/p\u003e\u003cp\u003e.- Utilizing Multiple Data Sources to Improve Prediction of Severe Weather Events through Spatio-Temporal Analysis.\u003c\/p\u003e","brand":"Springer","offers":[{"title":"Default Title","offer_id":51456262177111,"sku":"9783031961953","price":75.99,"currency_code":"GBP","in_stock":true}],"url":"https:\/\/bookcurl.com\/products\/engineering-applications-of-neural-networks-9783031961953","provider":"Book Curl","version":"1.0","type":"link"}