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Ever wondered why a feedforward neural network isn’t ideal for image classification? Here’s a quick explainer on its downsides and why convolutional layers make all the difference. Full tutorial is up on YouTube @TensorsAndTea. #ai #deeplearning #technology
1:54
TikToktensorsandtea
Ever wondered why a feedforward neural network isn’t ideal for image classification? Here’s a quick explainer on its downsides and why convolutional layers make all the
Tensors & Tea(@tensorsandtea). original sound - Tensors & Tea. Ever wondered why a feedforward neural network isn’t ideal for image classification? Here’s a quick explainer on its downsides and why convolutional layers make all the difference. Full tutorial is up on YouTube @TensorsAndTea. #ai #deeplearning #technology
413 views4 days ago
Feed forward Neural Networks
Animated Explanation of Feed Forward Neural Network Architecture - MLK - Machine Learning Knowledge
Animated Explanation of Feed Forward Neural Network Architecture - MLK - Machine Learning Knowledge
machinelearningknowledge.ai
Oct 30, 2019
Implementing feedforward neural networks with Keras and TensorFlow - PyImageSearch
Implementing feedforward neural networks with Keras and TensorFlow - PyImageSearch
pyimagesearch.com
May 6, 2021
Feed-forward Neural Networks for Pattern Recognition - SlideServe
Feed-forward Neural Networks for Pattern Recognition - SlideServe
slideserve.com
59 views10 months ago
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ErTuĞ GÖZAYDIN on Instagram: "🧠Hem Yazılım hem Robot Tasarım özellikleri bakımından Inovate Award kazandıran ZAĞANOS FTC robotumuzun özellikleri: Zağanos FTC robotu, hız, isabet ve kesintisiz skor prensipleriyle tasarlanmıştır. Dikey motor yerleşimli mekanum şasi, özel üretilmiş tekerler ve poliüretan kayışlı intake sistemi ile sahada akıcı, kararlı ve hızlı bir toplama kabiliyeti sunar. En önemli mekanik avantajı olan 270° dönebilen hafif taret, şasi hareket ederken hedefe kilitlenerek atış
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ErTuĞ GÖZAYDIN on Instagram: "🧠Hem Yazılım hem Robot Tasarım özellikleri bakımından Inovate Award kazandıran ZAĞANOS FTC robotumuzun özellikleri: Zağanos FTC robotu, hız, isabet ve kesintisiz skor prensipleriyle tasarlanmıştır. Dikey motor yerleşimli mekanum şasi, özel üretilmiş tekerler ve poliüretan kayışlı intake sistemi ile sahada akıcı, kararlı ve hızlı bir toplama kabiliyeti sunar. En önemli mekanik avantajı olan 270° dönebilen hafif taret, şasi hareket ederken hedefe kilitlenerek atış
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辻 二郎 on Instagram: "胸郭で受け、神経で安定させる。 Coiling Core × Med Ball Reaction ランジ姿勢で大きなメディシンボールをキャッチする。この動作の本質は「外力に対して力で抗う」ことではなく、神経で“統合して適応する”能力を育てることにある。 🧠神経学的メカニズム ランジ姿勢は、左右非対称の支持構造をつくり、骨盤と胸郭に異なる回旋トルクを発生させる。このとき、左股関節の求心性入力(afferent input)と右胸郭の遠心性出力(efferent drive)が同時に働き、体幹の交差的神経連鎖(Crossed Neuromuscular Pathway)が形成される。 メディシンボールをキャッチする瞬間、外力は胸郭の立体構造を通じて全身へ波のように伝わる。脊柱起立筋・腹斜筋群・広背筋が立体的に協応し、小脳歯状核(dentate nucleus)と前庭小脳が姿勢安定と運動誤差修正を即座に実行する。 このとき、前庭核(vestibular nuclei)は頭部加速度を感知し、視覚系(VOR:前庭動眼反射)と連動して視線を安定化。頭頂連合
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辻 二郎 on Instagram: "胸郭で受け、神経で安定させる。 Coiling Core …
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久田 哲也🥊ボクシングコーチ【HISADA ReBorn Boxing】 on Instagram: "『なぜボクサーはパンチをよける事が出来るのか?』 ボクサーのパンチは人間の反応速度を上回る! 【参考・出典】 ※1 人間の反応速度(視覚刺激に対する平均反応時間) 出典: ・日本自動車研究所(JARI)「ヒトの反応時間に関する研究」 平均値:約0.18〜0.25秒(視覚刺激に対して) ⸻ ※2 パンチの速度 出典: ・Walilko, T. J. et al. (1983). The damaging punch. Journal of Sports Medicine and Physical Fitness. PubMed ID: 3936571 → 0.49mの距離を約0.1秒で移動(速度8.9 m/s) → エリートボクサー平均速度9.8 ± 2.3 m/s ⸻ 【補足】 距離が約50cmの場合、パンチはおよそ0.1秒で届く計算になります。 人間の反応速度(約0.2秒)では間に合わないため、ボクサーは「予測」と「パターン認知」によって動いています。 これを「フィードフォワー
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