AI SIMULATED FAUX IMAGE DETECTION SYSTEM USING DEEP LEARNING

 Journal of Nonlinear Analysis and Optimization  Vol. 15, Issue. 1, No.12 :  2024  ISSN : 1906-9685

AI SIMULATED FAUX IMAGE DETECTION SYSTEM USING DEEP LEARNING

ABSTRACT –  Although biometric technology is essential for identifying people, thieves are always evolving to avoid being caught. We are using a state-of-the-art method called Deep Texture Features extraction from photos to tackle this problem. Building a Convolutional Neural Network (CNN) is our method for efficiently utilizing this technology. Known as LBPNET, this CNN-based model emphasizes the use of the Local Binary Pattern (LBP) methodology for feature extraction, making it stand out as a cuttingedge approach in the industry. To counter the spread of fake face photos in identification systems, we train the machine learning model to understand LBP descriptors taken from images. Our technique promises to improve the accuracy and dependability of facial recognition systems by integrating CNN technology with LBP descriptors, hence reducing the risk associated with fraudulent modifications to physical and psychological traits. 

KEYWORDS:  Deep textures, CNN, NLBPNet, LBPNet, LBP descriptor images. 

PAPER : Trace mortal pursuit framework using AI

 

Trace mortal pursuit framework using AI

ABSTRACT - Computer interfaces novelties are noticeable to expand AI based technology. Human actions and movements are recorded, tracked, and noticed with the help of AI based expert systems. NLP, ML, and its techniques are owned for tracking of human behaviours, according to the cautions that are generated in crucial time of situations will assist the mortals. To restrain emergency situations, AI based set-up and its mode are popular in human way of life. Surveillances gadgets are required around-the-clock to track record in the form of facts that are analysed using computer visionary techniques, NLP is utilized to recognize the human behaviour speech to diagnosis the circumstances and act according to posies. RNN with LSTM techniques are exercised and examine to execute the framework.

 Keywords: NLP, facts, RNN, LSTM, examine, framework.

"TRACE MORTAL PURSUIT FRAMEWORK USING AI", Dr.V.Shanmukha Rao,Md.Imran,D.S. Srinivas,D. Varun Prasad, Juni Khyat ISSN: 2278-4632 (UGC Care Group I Listed Journal) Vol-13, Issue-04, No.06, April : 2023 Page | 17 DOI: 10.36893.JK.2023.V13I04N16.0017-0022 

http://junikhyatjournal.in/no_1_Online_23/3s_apr.pdf

http://junikhyatjournal.in/no_1_Online_23.html

PAPERS: Analyzing of human facial bearings from facial emotion detection framework using Deep Learning

 

Analyzing of human facial bearings from facial emotion detection framework using Deep Learning

ABSTRACT- Aspirations are increased perilously with the contemporary technology in these days; Deep learning techniques are driven to develop various types of applications in and around computer vision. HCI systems are designed to analyze various human emotions that will help to study and analyze human behaviors. In Artificial intelligence, CNN and DNN models are pinpoint and trained to test to detect the emotions of human face and extracting their facial features. Mankind emotions such as annoyance, aversion, panic, satisfaction, unhappiness, revelation and so forth. Features are classified and analyzed using emotion recognition methodologies. The frameworks will be recognized and evaluated to generate the various results of samples that will help in investigating the human facial bearings and its instances that are used in a wide variety of HCI applications.

Keywords: HCI, CNN, DNN, Framework, bearings, instances

"ANALYZING OF HUMAN FACIAL BEARINGS FROM FACIAL EMOTION DETECTION FRAMEWORK USING DEEP LEARNING", Dr.V.Shanmukha Rao,Md.Imran,D.S. Srinivas,D. Varun Prasad, Dogo Rangsang Research Journal UGC Care Group I Journal, ISSN : 2347-7180 Vol-13, Issue-4, No. 20, April 2023 Page | 244 DOI: 10.36893.DRSR.2023.V13I0.0244-0249 

https://www.journal-dogorangsang.in/no_1_Online_23/37s.pdf

https://www.journal-dogorangsang.in/no_1_Online_23.html

Bootcamp on CYBER SECURITY

 

SUPRAJA TECHNOLOGIES IN ASSOCIATION WITH ALIET

3 Days Practical Hands-on Bootcamp on CYBER SECURITY & next followed by a 8 Hrs OR 12 Hrs OR 16 Hrs OR 24 Hrs HACKATHON 

11-04-2023 TO 13-04-2023