International Journal of Human Computations & Intelligence

Automated Detection of Large Animals in Road Scene Environments Using Deep Learning

2025-05-16T06:24:29+00:00

Automated detection of large animals in road scenes plays a crucial role in enhancing the safety of autonomous vehicles, particularly in regions where wildlife-related accidents are common. This paper introduces a deep learning-based explanation for detecting and classifying ten large animal classes within road scene environments, such as dogs, horses, cows, and bears. A specialized dataset was fetched using selected classes from the COCO and Open Images V5 datasets, annotated in the COCO format. Four advanced object detection models were trained and evaluated with the EfficientDet-D1, RetinaNet R-50-FPN, Faster R-CNN R-50-FPN, and Cascade R-CNN R-50-FPN. Results show that RetinaNet R-50-FPN achieved the highest mean Average Precision (mAP) of 0.83 for one joint class and 0.69 for ten classes while also delivering the fastest inference speed at 50.6 FPS for one-class detection and 45.2 FPS for multi-class detection. EfficientDet-D1 achieved a mAP of 0.89 for one joint class and 0.77 for ten classes, offering competitive performance but with slightly slower inference speeds. The findings highlight RetinaNet as the most effective and efficient model for real-time large animal detection in road scenes, offering significant potential for integration into modern autonomous driving systems.

Deep Defender: Smart detection of phishing websites

2025-05-16T07:31:21+00:00

Phishing is a consistent threat causing internet users to provide sensitive details in fictitious network environments. Current detection tools tend to sacrifice accuracy and timeliness of response, in doing which the threat exposure level is increased for the users. Here is presented a system based on machine learning intended to detect phishing URLs in the moment, with the aim of enhancing general online footprint safety.Based on the RNN-GRU algorithm, the system tries to maximize the effectiveness and promptness of phishing URL detection. The introduction of this approach brings an effective shield against phishing, a considerable increase in users protection in the digital era.

Integrating Artificial Intelligence & IoT for Precision Farming: Advancing Agriculture 4.0 Solutions

2025-05-30T14:25:48+00:00

Agriculture 4.0 represents a revolutionary change in current farming methods, made possible by state-of- the art technologies including AI, IoT, etc. This technology driven farming is called precision farming, which attempts to improve the operations and maximize the yields of agriculture and minimize the waste, while taking care of sustainable farming. In this paper we discuss the role of AI and IoT in precision agriculture, with a particular focus on the structure of smart farming systems, signiﬁcant technical aspects, and examples of use in the real world. It also discusses the difficulties and future directions of AI-IoT convergence in agriculture, such as data security, connectivity, and scalability.