Dhruv Kumar Soni

A Machine Learning Approach for Android Malware Detection Using Static Permissions and API Features

Dhruv Kumar Soni, Ashu Taneja, Ankita Rana

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Deep Learning Based Retinal Disease Classification Using Convolutional Neural Networks

Dhruv Kumar Soni, Neeti Taneja, Ibrar Ahmed, Ashu Taneja

The wide-reaching issue of vision impairment and blindness stems from various diseases affecting the retina, this strengthens the need for such ailments to be diagnosed early in their course. This research paper describes an entirely computer-aided technique for the classification of a …

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Building Sustainable Urban Futures with AI and Digital Twins

Dhruv Kumar Soni, Ashu Taneja

This chapter illustrates actual use cases of creative technology transforming urban design and operations in top smart cities such as Dubai, Barcelona and Singapore. It also discusses the integration with emerging technologies such as the Internet of Things, blockchain, fifth-generation (5G) technology. …

Murine metastatic embryonal rhabdomyosarcoma survival and immune response with a total tumor RNA lipid particle aggregate vaccine.

Leighton Andrew Elliott, Andrece Powell, Lauren Lavender, Darrice S. Montgomery et autres

e14646 Background: Rhabdomyosarcoma (RMS) is the most common pediatric soft tissue sarcoma (STS) requiring intense multiagent chemotherapy in conjunction with surgical resection and radiation therapy for cure rates of only 70%. Patients with metastatic and recurrent disease experience dismal chances of long-term …

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Deep Learning-Driven Classification of Acute Lymphoblastic Leukemia Subtypes Using CNNs

Dhruv Kumar Soni, Ashu Taneja, Komuravelly Sudheer Kumar, Mohammed I. Habelalmateena

In this paper, a Convolutional Neural Network (CNN) based model is created to differentiate blood cell images into the benign and malignancy classes with more emphasis on subtype of acute lymphoblastic leukemia (ALL). The model is trained on a dataset of 3,242 …

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Facial Emotion Recognition with CNNs: Analyzing Accuracy and Demographic Factors

Dhruv Kumar Soni, Ashu Taneja

Facial emotion recognition (FER) has become a basic issue of research in computer vision and has major applications in fields including mental health analysis, human-computer interface, security, and customer experience. Since facial expressions change considerably depending on demographic diversity, lighting conditions, and …

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Enhancing Cancer Diagnosis: CNN-Based Classification of Lung and Colon Histopathological Images

Dhruv Kumar Soni, Ashu Taneja

Lung and colon cancers rank among the most common and lethal malignancies globally, rendering precise and prompt detection essential for enhancing patient prognoses. This study introduces a convolutional neural network (CNN) methodology for the classification of lung and colon cancer utilising histopathology …

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Leveraging Transfer Learning and Synthetic Datasets for Multi-Class Insect Identification

Dhruv Kumar Soni, Ashu Taneja

This paper provides a synthetic dataset based on deep learning and transfer learning approach for insect classification. Programmatically created, 10,000 images in all 10 insect classes including bees, beetles, butterflies, cicada, dragonflies, grasshoppers, moths, scorpions, snails, and spiders. Combining segmented bug photos …

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Automated Detection of Poultry Diseases Using Deep Learning and Computer Vision

Dhruv Kumar Soni, Ashu Taneja, Komuravelly Sudheer Kumar, Zaeid Ajsan Salami et autres

Early, accurate detection of chicken diseases is necessary for promoting sustainable farming techniques, enhancing poultry health, and lowering of economic losses. This paper presents a deep learning-based method using transfer learning with the EfficientNetB5 architecture to classify chicken health issues into four …

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Leveraging EfficientNetB3 for Automated Plant Stress Identification

Dhruv Kumar Soni, Ashu Taneja

Automated plant stress diagnosis using EfficientNetB3 architecture eliminates agricultural constraints of conventional manual inspection methods. This paper demonstrates that EfficientNetB3 can identify many stress situations including insect infestations, nutrition deficits, and drought. The model obtained an incredible 98.2% accuracy using a diverse …

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Enhancing performance of in-vehicle network protocols for intelligent transportation

Dhruv Kumar Soni, Ashu Taneja

With the advancement of automotive industry, the number of sensors, electronic control units (ECUs), and actuators within the vehicle has increased. These ECUs need to communicate with each other and other system components within the vehicle to ensure efficient vehicle operation. For …

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Throughput analysis of IoT enabled intra vehicular wireless network

Dhruv Kumar Soni, Ashu Taneja

The increasing number of sensors and electronic systems in modern vehicles has led to the need for efficient intra-vehicular communication networks. Integrating the Internet of Things (IoT) concept with Intra-Vehicular Wireless Network Sensors (IVWNSs) presents an opportunity to create smart and connected …

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