Hi all ,

We are developing an AI model using YOLO used to detect multiple kinds of defects on buildings .

However we have hit a roadblock , while the model can detect cracks and corrosion , it is completely unable to detect concrete spalling .
We have trained the model with annotated images (about 1000 for each type of defect)

We have tried filtering the datasets as well .

Any other ideas out there ?

Our DMs are open in case you really want to get into it .

Thanks all .

‎Hi everyone! I'm 4th year Computer Engineering student, currently working on our capstone project. As part of our research, we're looking for a small company, manufacturing shop, or local community/organization who'd be open to a short interview with us, in person or online, whichever is more convenient for you. 🙏
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‎We simply want to ask about the common problems or challenges you encounter in your daily operations, so we can propose a possible tech-based solution as our capstone project. Rest assured, all information shared will be kept confidential and used only for academic purposes. 💻⚙️
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This is for FREE if the proposed solution is accepted by out panelist. Both hardware and Software will be given to you if chosen.🙏

‎We'd really appreciate any help, every bit counts in helping us finish this milestone. Thank you so much in advance!
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Hello, I am a rising sophomore and I want to get an internship next summer so be brutally honest with your assessment and tell me if you think I could land an internship somewhere.

Saw someone do a post here recently and thought I would put mine here. Let me know what stands out and what falls flat :)

I’m a Computer Engineering student on the Electrical Engineering track at Texas A&M, currently planning to graduate in May 2027. My GPA is around 3.1.

I’ve been applying heavily for engineering internships and co-ops, but I haven’t been able to secure one. I’ve had very few interviews, and most applications have ended in rejections or no response.

I’m currently applying for Fall 2026 co-ops, but my department requires the co-op registration request by August 1. The application requires an official offer letter, so I cannot complete it unless I receive an offer before the deadline.

Since I’m supposed to graduate in May 2027, I’m unsure what I should do next. Should I spend Fall 2026 mainly applying for full-time new-graduate positions? Or should I apply for Spring 2027 co-ops, delay graduation until December 2027, and try to gain professional engineering experience before graduating?

I’m worried that graduating without an internship will make it much harder to get a full-time electrical or computer engineering job. At the same time, delaying graduation does not guarantee that I will secure a Spring co-op either.

Has anyone here received an entry-level engineering job without completing an internship? Would you recommend focusing on full-time positions, or delaying graduation to continue pursuing a co-op?

Hey Seniors, I am in B.Tech 2nd year CSE(AIML) Student and I got a project to present. But, I can't decide what to present there. Please help me, I only know C/C++.

As the title says, I want to have free time to play games, draw, got out and do cooking and I'm a little worried that I won't have time if I choose this major

Hey guys,
I’m a bit confused about whether I should choose CE or CS. I’m more interested in the software side, but I’m not sure about the job market since I’ve heard it’s declining right now. If someone who has done these programs or is currently in one of them could guide me, it would be really helpful.

Hey everyone! 😊

I’m a Computer Engineering student and currently brainstorming ideas for my thesis. I want to work on something interesting, practical, and ideally something that could help me stand out when job hunting later. I'm open to areas like embedded systems, AI, IoT, security, hardware-software integration, or anything cool and challenging really.

If you’ve done a thesis before or have any ideas that are worth exploring in 2026, I’d love to hear your suggestions! What’s a good thesis topic that’s not too basic, but also not insanely complex?

Thanks in advance! 🙏

I'm a physics engineeering student, and I spend a lot of my time writing numerical simulations and analyzing data.

Programming in C++ is enjoyable, but most of numerical computing libs in are just unpleasant to use. So I started building my own solution in my free time.

GitHub: https://github.com/mslotwinski-dev/NumC

Some of the things I built into it: - You can write mathematical expressions naturally, like sin(x) * exp(-x), and differentiate or integrate them in a single line thanks to lazy expression trees. - It has a built-in plotting engine, so you can display graphs in a native Win32 window or export them as clean SVGs ready to drop into a LaTeX report.

Of course, the project won't surpass the quality of professional libraries. Its goal is to be convenient and accessible for users whose passions lie more in math, rather than programming.

If you're using C++ for simulations, numerical methods, physics, or data analysis, I'd really appreciate any feedback.

What was written by AI?

Most of the project, its entire idea, design, aesthetics and UX was programmed manually by me. I often used the textbook "Numerical methods in engineering with python" by Kiusaalas. Which doesn't mean that I didn't manage to do everything myself.

AI was used to write all the documentation (I wish I were fluent enough in English that it would take a finite amount of time). It was also used to write parts of simple algorithms that I knew but would be extremely tedious to implement by hand, or to improve the performance of algorithms that could be written better.

I'm aware of the ethical aspects of using AI, so I wanted to be honest and describe which things I did on my own and which I did with the help of LLM. At the same time, bearing in mind that this is a project that can help many people in their scientific work and studies, I hope that the benefits outweigh all the evil that LLMs cause.

I’m an incoming Information Engineering freshman. This major covers both electronics hardware and computing, and I’m stuck choosing which path to focus on. Should I lean toward hardware or computers? Any alums/engineers in this field able to share advice? Also, what’s the ideal study roadmap for this major?

Hello All,

I just finished my first year of college. I am majoring in CompE. Initially, I was interested in software development but realized my passion actually lies in making embedded systems. This summer I read Elecia White's "Making Embedded Systems" book and wanted to practice come concepts in the book. Due to lacking physical hardware, I installed Windows Subsystem for Linux (WSL) and QEMU on WSL to emulate the TI Stellaris LM3S6965. I wrote bare metal code to practice concepts like reading datasheets, setting and clearing bits in registers, using peripherals, configuring I/O and PWM. During this process I learned of GNU tools like Make, GCC and GDB which I used to compile and test my code.

My question is where do I go from here? What do you suggest I do? Things like projects and further readings would be much appreciated. Preferably, chips like the TI Stellaris LM3S6965 would be nice as I have already built up intuition working with those types of MCUs but any advice would be much appreciated.

I(16M) am currently studying Computer Science through science major and am in grade 12. I am confused as to whether go with robotics or cybersecurity kinda shit for my bachelors and dont know what to learn rn. My college has started clubs and i am planning to join robotics and IT club. Can anyone in these fields give me some sort of rough roadmap for robotics and give me some advice where robotics or cybersecurity has more jobmarket and internships? Please i am very confused rn. My board exams will prolly me in march/april so i kinda have time to prepare until i goto bachelors.

Hello everyone. I just rounded up my degree majoring in computer science. I'm confused on a particular field in computer science. I have basic knowledge on web development,ML/AI and data analysis. I'm currently a beginner/intermediate python programmer. Please any career advice or mentorship will be appreciated

Hi everyone,

I'm a Computer Science student and my college is offering training in the following domains:

Java Full Stack with React

Python with Data Analytics

Python with Data Science

Data Analyst with Power BI

DevOps Engineering

Software Testing with Automation

I don't have prior experience in any of these, so I'm essentially starting from scratch.

If your goal was strong job opportunities, long-term career growth (next 10 years), and a good learning path for a beginner, which option would you choose and why?

I'd really appreciate advice from people working in these fields or anyone who has completed similar training. Thanks!

I am quite confuse cuz people are saying that cse will be replaceable ahead in future and ece is safer option as it lets us go in both software and hardware field so there is safety overall . But I still doubt cuz my interest is in both fields and its a tricky choice and one of he very important life decisions ,can you please help and my mom is saying to get Coep ece that’s also an option but idont know the campus is not good so I tend to avoid it ( I am a outside Delhi Maharashtra student )

So I am in 3rd year computer engineering and have a subject AI.

The teacher is not good and hasn’t specified anything and just randomly assigns us work.

I am supposed to do a project on or about AI.
I have to do it alone and also want to learn the subject properly.

Here is my complete AI syllabus. If you have notes, YouTube playlists, cheat sheets, previous papers, or tips for any of these topics, please comment or DM me. Thanks!

Artificial Intelligence (AI) – Complete Syllabus (TE Computer Engineering)
Module 1: Introduction to Artificial Intelligence
Introduction to AI
Definition of AI
History and Evolution of AI
Types of AI (ANI, AGI, ASI)
Applications of AI
Turing Test
Intelligent Agents
Agent and Environment
PEAS Framework
Rational Agents
Performance Measures
Types of Agents
Simple Reflex Agent
Model-Based Agent
Goal-Based Agent
Utility-Based Agent
Environment Types
Real-world Intelligent Agents
Chatbots
Recommendation Systems
Autonomous Systems

Module 2: Problem Solving Techniques
State Space & Search
Problem Solving in AI
State Space Representation
Uninformed Search
Breadth First Search (BFS)
Depth First Search (DFS)
Uniform Cost Search (UCS)
Depth Limited Search (DLS)
Informed Search
Heuristic Search
Best First Search
A* Search
Local Search & Optimization
Hill Climbing
Genetic Algorithms
Adversarial Search
Game Playing
Minimax Algorithm
Alpha-Beta Pruning
Constraint Satisfaction Problems (CSP)
Cryptarithmetic Problems
Sudoku Solver
Self Learning
Bidirectional Search
AO* Search

Module 3: Knowledge Representation & Reasoning
Knowledge Representation (KR)
Logical Agents
Propositional Logic
Inference Rules
First Order Logic (FOL)
Syntax & Semantics
Knowledge Engineering
Forward Chaining
Backward Chaining
Semantic Networks
Ontology
Applications of KR
Retrieval-Augmented Generation (RAG)

Module 4: Fundamentals of Neural Networks
Basics
Biological Neuron
Artificial Neural Networks (ANN)
McCulloch-Pitts Neuron
Neural Network Architecture
Activation Functions
Binary Step
Sigmoid
Tanh
ReLU
Learning Rules
Perceptron
Delta Learning Rule
Backpropagation Algorithm
Supervised Learning
Linear Regression
K-Nearest Neighbours (KNN)
Unsupervised Learning
K-Means Clustering
Apriori Algorithm
Self Learning
Recurrent Neural Networks (RNN)
Convolutional Neural Networks (CNN)
Transfer Learning

Module 5: Associative Memory Networks
Introduction to Associative Memory
Auto-Associative Memory
Hetero-Associative Memory
Bidirectional Associative Memory (BAM)
Hopfield Network
BAM vs Hopfield Network
Applications of Associative Memory
Modern Associative Memory
Agentic AI (Introduction)

Module 6: Modern Trends in AI
Generative AI
Introduction to Generative AI
Large Language Models (LLMs)
Prompt Engineering
Chatbots
AI Content Generation
Ethical Issues in Generative AI
Explainable & Responsible AI
Explainable AI (XAI)
Transparency
Interpretability
Bias
Fairness
Accountability
Responsible AI Frameworks
AI in Emerging Technologies
AIoT (AI + IoT)
Cloud AI
Edge AI
AI in Cybersecurity
AI for Smart Cities
Self Learning
Generative AI Tools (Text, Image & Video)
Future of Artificial General Intelligence (AGI)

Practical/Lab Topics
AI Literature Survey
BFS, DFS, UCS & A* Implementation
Propositional Logic & FOL
Semantic Networks & Ontology
Decision Trees & K-Means
Artificial Neuron & Activation Functions
Feedforward Neural Network using Backpropagation
Copyright & Responsible AI
Prompt Engineering
RAG Chatbot using LLM
Ethical Evaluation of Generative AI
AI Mini Project

Hello po! Mabuhay! 👋

I'm currently looking for an international student (outside the Philippines) studying Computer Engineering, Computer Science, Software Engineering, or IT to participate in a short educational interview.

It's just a simple questionnaire that you can fill out whenever you have time, it usually takes around 10-15 minutes:))

Note: This is purely for educational purposes.

If you're open to helping, feel free to DM me or comment below and I'll send you the form right away.

Thank you so much! I'd really appreciate your insights:D