AIMC Topic: Animals

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LPAI-A Complete AIoT Framework Based on LPWAN Applicable to Acoustic Scene Classification Scenarios.

Sensors (Basel, Switzerland)
Deploying artificial intelligence on edge nodes of Low-Power Wide Area Networks can significantly reduce network transmission volumes, event response latency, and overall network power consumption. However, the edge nodes in LPWAN bear limited comput...

A robotic model of hippocampal reverse replay for reinforcement learning.

Bioinspiration & biomimetics
Hippocampal reverse replay, a phenomenon in which recently active hippocampal cells reactivate in the reverse order, is thought to contribute to learning, particularly reinforcement learning (RL), in animals. Here, we present a novel computational mo...

Deep Learning-Powered Bessel-Beam Multiparametric Photoacoustic Microscopy.

IEEE transactions on medical imaging
Enabling simultaneous and high-resolution quantification of the total concentration of hemoglobin ( [Formula: see text]), oxygen saturation of hemoglobin (sO2), and cerebral blood flow (CBF), multi-parametric photoacoustic microscopy (PAM) has emerge...

Robot-Assisted Radical Nephrectomy Using the Novel Avatera Robotic Surgical System: A Feasibility Study in a Porcine Model.

Journal of endourology
To evaluate the feasibility and intraoperative technical parameters of the new robot-assisted surgical system Avatera by performing bilateral nephrectomy in a live porcine model. Six pigs underwent bilateral robot-assisted radical nephrectomy using...

A novel hybrid optimization enabled robust CNN algorithm for an IoT network intrusion detection approach.

PloS one
Due to the huge number of connected Internet of Things (IoT) devices within a network, denial of service and flooding attacks on networks are on the rise. IoT devices are disrupted and denied service because of these attacks. In this study, we propos...

Toward Region-Aware Attention Learning for Scene Graph Generation.

IEEE transactions on neural networks and learning systems
Scene graph generation (SGGen) is a challenging task due to a complex visual context of an image. Intuitively, the human visual system can volitionally focus on attended regions by salient stimuli associated with visual cues. For example, to infer th...

Case Study: Improving the Quality of Dairy Cow Reconstruction with a Deep Learning-Based Framework.

Sensors (Basel, Switzerland)
Three-dimensional point cloud generation systems from scanning data of a moving camera provide extra information about an object in addition to color. They give access to various prospective study fields for researchers. With applications in animal h...

Deep learning-based diagnosis of stifle joint diseases in dogs.

Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association
In this retrospective, analytical study, we developed a deep learning-based diagnostic model that can be applied to canine stifle joint diseases and compared its accuracy with that achieved by veterinarians to verify its potential as a reliable diagn...

A large-scale neural network training framework for generalized estimation of single-trial population dynamics.

Nature methods
Achieving state-of-the-art performance with deep neural population dynamics models requires extensive hyperparameter tuning for each dataset. AutoLFADS is a model-tuning framework that automatically produces high-performing autoencoding models on dat...

Characterisation of urban environment and activity across space and time using street images and deep learning in Accra.

Scientific reports
The urban environment influences human health, safety and wellbeing. Cities in Africa are growing faster than other regions but have limited data to guide urban planning and policies. Our aim was to use smart sensing and analytics to characterise the...