Diagnosis of Brain Tumor Using Light Weight Deep Learning Model with Fine-Tuning Approach

Article Mathematical & Computational Biology

Real-Time Twitter Spam Detection and Sentiment Analysis using Machine Learning and Deep Learning Techniques

Anisha P. Rodrigues et al.

Summary: The proposed work aims to develop a system that can determine whether a tweet is spam or ham and evaluate its emotion. Through sentiment analysis, the problem of spam accounts on social media sites can be effectively addressed.

COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE (2022)

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Article Mathematical & Computational Biology

Enhancement of Detection of Diabetic Retinopathy Using Harris Hawks Optimization with Deep Learning Model

Nagaraja Gundluru et al.

Summary: Diabetic retinopathy is a severe health issue that can lead to vision loss and blindness. By utilizing a deep learning model with PCA and Harris hawks optimization algorithm, the feature extraction and classification process can be optimized, resulting in improved accuracy and precision.

COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE (2022)

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Article Construction & Building Technology

Zero knowledge proofs based authenticated key agreement protocol for sustainable healthcare

Gurjot Singh Gaba et al.

Summary: The upgradation of technologies for sustainable smart cities has resulted in the rapid growth of IoT applications in healthcare. However, the vulnerability of the wireless channel for communication poses a risk of unauthorized access to confidential medical information. This paper proposes a scheme based on zero-knowledge proofs and authenticated key agreement protocol to protect confidentiality and anonymity in IoT healthcare applications.

SUSTAINABLE CITIES AND SOCIETY (2022)

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Review Computer Science, Information Systems

A Review on Deep Learning Techniques for IoT Data

Kuruva Lakshmanna et al.

Summary: Continuous growth in software, hardware and internet technology has enabled the growth of internet-based sensor tools that provide physical world observations and data measurement. The Internet of Things (IoT) is made up of billions of smart things that communicate, extending the boundaries of physical and virtual entities of the world further. Deep learning has been identified as a potential solution to manage the vast amount of data generated by IoT due to its ability to handle large amounts of diverse data, requiring almost real-time processing. This paper explores the use of deep learning techniques in IoT to further develop intelligence and application capabilities, discussing various approaches and summarizing major reporting efforts in the field.

ELECTRONICS (2022)

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Article Computer Science, Artificial Intelligence

Deep Learning for Multigrade Brain Tumor Classification in Smart Healthcare Systems: A Prospective Survey

Khan Muhammad et al.

Summary: This overview reviews deep learning-based methods for brain tumor classification, covering preprocessing, feature extraction, and classification steps, along with their applications and limitations in diagnostic analysis by radiologists. The study also investigates the impact of the latest convolutional neural network models on brain tumor classification through experiments, and explores future directions in personalized and smart healthcare.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2021)

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Article Computer Science, Artificial Intelligence

Hand gesture classification using a novel CNN-crow search algorithm

Thippa Reddy Gadekallu et al.

Summary: The study implements a crow search-based convolutional neural network model for gesture recognition in the HCI domain, achieving impressive results. By converting data using one-hot encoding and selecting optimal hyper-parameters with CSA, the model is optimized to enhance accuracy in classifying hand gestures, ultimately achieving 100% training and testing accuracy.

COMPLEX & INTELLIGENT SYSTEMS (2021)

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Article Chemistry, Analytical

MRI-Based Brain Tumor Classification Using Ensemble of Deep Features and Machine Learning Classifiers

Jaeyong Kang et al.

Summary: The study proposed a method for brain tumor classification using deep features and machine learning classifiers, adopting the concept of transfer learning and pre-trained deep convolutional neural networks. Experimental results demonstrated that an ensemble of deep features can significantly improve performance, with support vector machine outperforming other classifiers on large datasets.

SENSORS (2021)

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Article Computer Science, Information Systems

VGG-SCNet: A VGG Net-Based Deep Learning Framework for Brain Tumor Detection on MRI Images

Mohammad Shahjahan Majib et al.

Summary: A brain tumor is a life-threatening neurological condition caused by unregulated cell growth in the brain or skull, with early diagnosis being crucial for survival. Traditional methods for identifying brain tumors are time-consuming and rely heavily on expert knowledge, hence the importance of computer-assisted techniques.

IEEE ACCESS (2021)

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Article Computer Science, Information Systems

Filtered Multicarrier Waveforms Classification: A Deep Learning-Based Approach

Kawtar Zerhouni et al.

Summary: This paper proposes two deep learning-based automatic signal recognition methods, one based on support vector machine (SVM) and the other based on CNN, without requiring prior knowledge, concluding that CNN outperforms cyclicality features in short-time received signals and low SNR levels.

IEEE ACCESS (2021)

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Article Computer Science, Information Systems

Machine Learning and Deep Learning Approaches for Brain Disease Diagnosis: Principles and Recent Advances

Protima Khan et al.

Summary: The brain is the controlling center of the body and with the advancement of artificial intelligence in medical science, more accurate prediction and detection of brain diseases can be achieved. This study reviews recent machine learning and deep learning approaches in detecting Alzheimer's disease, brain tumor, epilepsy, and Parkinson's disease to find the most accurate technique for future improvement.

IEEE ACCESS (2021)

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Article Automation & Control Systems

Roughsets-based Approach for Predicting Battery Life in IoT

Rajesh Kaluri et al.

Summary: The Internet of Things and its related applications have enhanced the value of life on Earth and face the challenge of energy optimization. Utilizing a Deep Neural Network model for optimized predictions in the marine environment battery life sustainability, the superiority of the proposed model was demonstrated through comparison with state of the art machine learning models.

INTELLIGENT AUTOMATION AND SOFT COMPUTING (2021)

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Article Engineering, Electrical & Electronic

A Deep Learning-Based Framework for Automatic Brain Tumors Classification Using Transfer Learning

Arshia Rehman et al.

CIRCUITS SYSTEMS AND SIGNAL PROCESSING (2020)

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Article Computer Science, Artificial Intelligence

Brain tumor detection using fusion of hand crafted and deep learning features

Tanzila Saba et al.

COGNITIVE SYSTEMS RESEARCH (2020)

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Article Computer Science, Artificial Intelligence

A classification method for brain MRI via MobileNet and feedforward network with random weights

Si-Yuan Lu et al.

PATTERN RECOGNITION LETTERS (2020)

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Article Computer Science, Artificial Intelligence

Hybrid genetic algorithm and a fuzzy logic classifier for heart disease diagnosis

G. Thippa Reddy et al.

EVOLUTIONARY INTELLIGENCE (2020)

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Article Computer Science, Information Systems

A Deep Learning Model Based on Concatenation Approach for the Diagnosis of Brain Tumor

Neelum Noreen et al.

IEEE ACCESS (2020)

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Article Engineering, Multidisciplinary

DETECTION AND CLASSIFICATION OF BRAIN TUMOURS FROM MRI IMAGES USING FASTER R-CNN

Ercan Avsar et al.

TEHNICKI GLASNIK-TECHNICAL JOURNAL (2019)

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Proceedings Paper Computer Science, Theory & Methods

CS-IBE : A Data Confidentiality System in Public Cloud Storage System

Ahmed Bentajer et al.

9TH INTERNATIONAL CONFERENCE ON EMERGING UBIQUITOUS SYSTEMS AND PERVASIVE NETWORKS (EUSPN-2018) / 8TH INTERNATIONAL CONFERENCE ON CURRENT AND FUTURE TRENDS OF INFORMATION AND COMMUNICATION TECHNOLOGIES IN HEALTHCARE (ICTH-2018) (2018)

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Article Computer Science, Artificial Intelligence