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⏩ Chapter:
00:00 Intro
01:18 Main ideas and concepts
03:18 Digital images
09:32 Available tools
11:09 Filters
13:05 CIImage
14:03 CIFilter
14:57 CIContext
16:00 Kernel
17:30 How to use Core Image Filters
18:58 Pay attention
20:15 Machine Learning & Image Processing
22:25 MNIST Specifics
23:50 How to Binarise an image
25:12 Otsu’s Method
26:35 Custom Kernel
31:50 The result
🤖 Apple encourages developers to improve their app user experience with on-device #machinelearning features, like object detection in images or handwriting recognition.
📊 However, user input quality on mobile is often different from the data used to #train models, so the results may be frustrating when using those models on raw data. It is especially applicable to images.
⚙️ This talk wants to propose a solution to this problem by implementing input image pre-processing on the device with nothing but #Swift and native frameworks.
🔑 We will discuss why image processing is #essential and how we can achieve the best results with available instruments.
🎤 Elina Semenko, Software Engineer, EPAM Systems
📍Swift Heroes 2023 was hosted in Turin, 4-5 May. Attended by 320 iOS developer participants and broadcast to an additional 320 Swift enthusiasts across the globe. The agenda covered a range of important iOS developer topics including SwiftUI, the composable architecture, accessibility, developer tools, testing and much more.
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#SwiftHeroes #SwiftProgramming #ImageProcessing #MachineLearning #AppDevelopment #iOSDev #MobileUX #SwiftUI #ObjectDetection #HandwritingRecognition #TechInnovation